Sleep Mode

The work presented in this thesis report is essentially for the completion of the Master degree in Communications and Computer Networks Engineering. This is the research based thesis report which I carried in Department of Electronics and Telecommunications, Politecnico di Torino. The work is performed under the supervision of Prof. Michela Meo and I would like to thank her for guiding me and reflecting positive energies that I always felt in every meeting and discussion with her. I would also like to thank my co-supervisor, Dr. Daniela Renga as she kept her door open for me and always encouraged and guided me throughout this time period. I learnt a lot under the supervision of both of them and this is the most memorable time during my master degree. Also, I want to thank my lab mates for making this research learning a bit easier through their motivation. Further, I want to thank my family. My parents, who are always there for me and without their support I would never be able to reach here. My sister and brothers who lifted me up with their motivation and love. I would also like to thank my friends in Italy and in Pakistan for boosting me up whenever i felt weak. Finally and for mostly, I would like to thank Allah Almighty, for keeping me in good health and blessing me with abilities and opportunities to perform better in life and for His unconditional love and mercy.

Cell standby, particularly picocell sleep mode (SM), is a prominent strategy for reducing energy consumption in 5G networks. The emergence of multi-state sleep states necessitates new optimization approaches. This paper proposes a novel energy optimization strategy for 5G heterogeneous networks (HetNets) that leverages macrocell-picocell coordination and machine learning. The proposed strategy focuses on managing the four available picocell sleep states. The picocell manages the first three states using the Q-learning algorithm, an efficient reinforcement learning technique. The associated macrocell based on picocell energy efficiency controls the final, deeper sleep state. This hierarchical approach leverages localized and network-wide control strengths for optimal energy savings. By capitalizing on macrocell-picocell coordination and machine learning, this work presents a promising solution for achieving significant energy reduction in 5G HetNets while maintaining network performance.

When evolved NodeB (eNB) flexible functional split is implemented in Virtualized Radio Access Network (V-RAN) 5G systems, fronthaul connectivity between the virtualized network functions (VNFs) must be seamlessly guaranteed. This study proposes the utilization of Software Defined Networking (SDN) to control the mobile fronthaul. In particular, this study investigates the ability of the SDN-based control of reconfiguring the fronthaul to maintain VNF connectivity when cell and optical access turn into sleep mode (off mode) for energy efficiency purposes. The evaluation of the proposed scheme is performed by federating two remote experimental testbeds. Results show that, upon cell and optical access turning on and off, the fronthaul reconfiguration time is limited to few tens of milliseconds.

The Suspended Gate Field Effect Transistor (SG-FET) appears to have the potential to replace traditional FETs in sleep mode circuits, due to its abrupt switching enabled by electromechanical instability at a certain threshold voltage and its ultra low "off" current (I off ). This paper presents a preliminary assessment of the SG-FET potential if utilized as sleep transistor in real applications, e.g., microprocessors. We first evaluate various SG-FET instances in terms of switching delay, current capability, and leakage. Subsequently, we compare these figures with the ones offered by traditional switch transistors utilized in CMOS technologies. Our simulation results indicate that SG-FET based sleep mode circuits are potentially interesting as they clearly enable substantial leakage reductions due to their extremely low "off" currents (4 orders of magnitude lower than FET) at the expense of a 4x larger active area for the same capability to drive current.

Cellular networks are optimized by targeting multiple objectives. Usually, the different objectives are not coherent: minimizing the transmit power; the number of base station (BS) sleep-mode switchings, ie, ACTIVE/SLEEP state transitions; and the activity of the BSs and guaranteeing the quality-of-service (QoS) of users. Hence, suitable trade-offs have to be managed by network planners to provide an efficient solution to the challenge of booming mobile data. In this paper, we propose a multiobjective optimization framework aimed at minimizing the power consumption and the number of BS sleep-mode switchings in cellular networks, by jointly considering QoS requirements. These requirements are expressed in terms of a required bit rate for each mobile terminal. The framework deals with network management, such as the number of BSs that should be switched on, considering common diurnal patterns of the traffic demand. The optimization technique proposed in this paper is mixed-integer quadratic programming, which solves the joint power allocation and user association problem while also considering optimized bandwidth allocation schemes. The trade-off between the conflicting objectives, as well as the performance analysis in terms of the throughput and energy consumption of the network, is shown for different traffic load cases. The proposed optimization can obtain up to 60% energy savings during off-peak hours, guaranteeing QoS target requirements. By optimizing the network configuration, a 70% reduction in BS switch on/off operations can be reached in a day with 3% more energy expense.

For reducing the energy consumption of the Mobile Station in mobile Broadband Wireless Access networks, IEEE 802.16 offers three kinds of sleep mode operations called power saving classes type I, type II and type III. In order to investigate mathematically the inherent relationships between the performance measures and the system parameters, we propose in this paper a novel method for modeling the sleep mode with the power saving class type II in IEEE 802.16 and analyzing the performance of this sleep mode. Considering the attractive feature that some data frames can be transmitted during the listening state, we present a queueing model with two kinds of busy mechanisms to capture the working principle of the sleep mode operations with the power saving class type II. With the first and higher derivatives of the probability generating functions, we can give the averages and the standard deviations for the system performance using the diffusion approximation for the operating process of the system. We also propose methods for measuring the system performance in terms of the switching ratio, the energy saving ratio, and the average response time of data frames, as well as giving the expressions for these performance measures. Numerical results are provided with analysis and simulation to show the average performance measures, standard deviations and the cost function with different system loads. Moreover, we construct a cost function with the aim of determining the optimal time length of the sleep window to minimize the cost function.

In this paper, we present an effective method to analyze the performance of the power saving class type III initiated by the base station with unsolicited MOB_SLP-RSP or DL sleep control extended subheader in a self-similar traffic. We build a batch arrival queueing model, in which the batch size is described by a random variable following a Pareto(c, a) distribution in order to capture the self-similar property in multimedia WiMAX based on the IEEE 802.16. By using the discrete-time embedded Markov chain, we can examine and analyze the power saving class type III systems for the following items: the probability generating functions of the number of data frames and batches when the busy period begins, the queueing length, the waiting time and finally the busy cycle. With the first and higher derivatives of the probability generating functions, we can give the averages and the standard deviations for the system performance using the diffusion approximation for the operation process of the system. Next, we give the formulas for the system performance such as the energy saving ratio, the switching ratio, the system utility and the response time of data frames. Moreover, we construct a cost function with the aim of determining the optimal sleep window length that minimizes the cost function. Numerical results are provided with analysis and simulation to show the average performance measures, standard deviations and a cost function with different degrees of self-similarity and different sleep window lengths.

The latest Very Large Scale Integration (VLSI) technology trends have been moving towards making devices cheaper and more powerful for everyone to afford them. So the ultimate focus being reducing power consumption by the gadgets. With the added feature of transistors to be structured in 3D, the Moore's law is to be continued. Hence, Leakage currents are a major concern with the increasing number of transistors per chip when the technology is scaled, static power dissipation needs to be monitored. Advanced RISC Machine (ARM) Processors have been giving a new definition to smart phones, tablets and other embedded applications. This paper presents a novel technique focusing on low power technology, developing an ARM7 microprocessor using Sleep transistor with Sub threshold Current Mode Logic (STCML) technique in 45nm technology using Cadence Virtuoso Tool. The simulation results have been observed on Spectre simulator and power has been calculated in Analog Design Environment (ADE L).

Broadcast disk technology has become a popular method for data dissemination in wireless information systems. However, factors such as intentional periodic disconnection by the mobile hosts result in further needs for managing access modes to let the mobile hosts procure highest benefit through the disconnections. In this paper, we propose a new broadcast indexing structure, Data Receiver Indicator (DRI), which allows mobile clients to determine the time interval of active and sleep mode for connection according to turnaround time. Our goal is to develop an intelligent data retrieve protocol that allows mobile users to acquire more valuable data with less power consumption within a limited turnaround time. Our performance results show that DRI substantially outperforms the traditional indexes and especially gets 75% saving on waiting time. Therefore, with our approach, users may acquire more valuable data with less power consumption and reduced waiting time which means faster query and response.

Most of existing works about sensor networks focus on energy management. Already proposed solutions often consist in balancing energy consumption by taking advantage of the redundancy induced by the random deployment of nodes; some nodes are active while others are in sleep mode, thus consuming less energy. Such a dynamical topology should not impact the monitoring activity. Area coverage protocols aim at turning off redundant sensor nodes in order to constitute a set of active nodes that covers as large an area as the whole set of nodes. In this paper, we focus on localized algorithms that require 1-hop knowledge only to allow nodes to choose their activity status. The unit disk model is the most commonly used assumption; if a node emits a message, any node within its communication range receives it while any node outside the disk does not. In this article, the impact of a realistic radio channel on area coverage protocols for wireless sensor networks is studied. It is shown that a non-binary reception probability can lead to very different results for protocols that could though provide great performances with the unit disk model. An optimization of a protocol to keep increasing the network lifetime once a realistic energy consumption model is considered is also provided.

Communication is the main motive in any Networks whether it is Wireless Sensor Network, Ad-Hoc networks, Mobile Networks, Wired Networks, Local Area Network, Metropolitan Area Network, Wireless Area Network etc, hence it must be energy efficient. The main parameters for energy efficient communication are maximizing network lifetime, saving energy at the different nodes, sending the packets in minimum time delay, higher throughput etc. This paper focuses mainly on the energy efficient communication with the help of Adjacency Matrix in the Wireless Sensor Networks. The energy efficient scheduling can be done by putting the idle node in to sleep node so energy at the idle node can be saved. The proposed model in this paper first forms the adjacency matrix and broadcasts the information about the total number of existing nodes with depths to the other nodes in the same cluster from controller node. When every node receives the node information about the other nodes for same cluster they communicate based on the shortest depths and schedules the idle node in to sleep mode for a specific time threshold so energy at the idle nodes can be saved.

We consider an idealistic scenario where the vacation (no-load) period of a typical base station (BS) is known in advance such that its vacation time can be matched with a sleep depth. The latter is the sum of the deactivation latency, actual sleep period and reactivation latency. Noting that the power consumed during the actual sleep period is a function of the deactivation latency, we derive an accurate closed-form expression for the optimal deactivation latency for deterministic BS vacation time. Further, using this expression, we derive the optimal average power consumption for the case where the vacation time follows a known distribution. Numerical results show that significant power consumption savings can be achieved in the sleep mode by selecting the optimal deactivation latency for each vacation period. Furthermore, our results also show that deactivating the BS hardware is sub-optimal for BS vacation less than a particular threshold value.

In this paper, we present an analytical framework to model the sleep mode power consumption of a base station (BS) as a function of its sleep depth. The sleep depth is made up of the BS deactivation latency, actual sleep period and activation latency. Numerical results demonstrate a close match between our proposed approach and the actual sleep mode power consumption for selected BS types. As an application of our proposed approach, we analyze the optimal sleep depth of a BS, taking into consideration the increased power consumption during BS activation, which exceeds its no-load power consumption. We also consider the power consumed during BS deactivation, which also exceeds the power consumed when the actual sleep level is attained. From the results, we can observe that the average total power consumption of a BS monotonically decreases with the sleep depth as long as the ratio between the actual sleep period and the transition latency (deactivation plus reactivation latency) exceeds a certain threshold.

This paper explores the feasibility of applying sleep-mode strategies in a realistic RAN network, using a deployment scenario from a local MNO as a case study. By modelling spatially correlated shadowing and 3GPP-compliant path loss, we evaluate individual and combined eNB coverage under both optimized and sequential activation schemes. Results show that optimisation significantly improves coverage at low activation levels, achieving near-complete service with fewer active sites. A fitted similarity model characterizes convergence between the two approaches, introducing a deployment-specific parameter α that helps guide practical energy-saving decisions based on traffic load. The proposed method offers both performance gains and planning insights for dynamic, energy-aware RAN control.

Recent studies show that peripheral circuit (including decoders, wordline drivers, input and output drivers) constitutes a large portion of the cache leakage. In addition, as technology migrates to smaller geometries, leakage contribution to total power consumption increases faster than dynamic power, indicating that leakage will be a major contributor to overall power consumption. This paper presents zig-zag share, a circuit technique to reduce leakage in SRAM peripherals by putting them into low-leakage power sleep mode. The zig-zag share circuit is further extended to enable multiple sleep modes for cache peripherals. Each mode represents a trade-off between leakage reduction and the wakeup delay. Using architectural control of multiple sleep modes, an integrated technique called MSleep-Share is proposed and applied in L1 and L2 caches. MSleep-share relies on cache miss information to guide leakage control mechanism and switch peripheral circuit's power mode. The results show leakage reduction by up to 40 in deeply pipelined SRAM peripheral circuits, with small area overhead and small additional delay. This noticeable leakage reduction translates to up to 85% overall leakage reduction in on-chip memories. Index Terms-Horizontal and vertical sleep transistor sharing, leakage power, multiple sleep modes, SRAM peripheral. C MOS technology scaling has been a primary driving force to increase the processor performance. A drawback of this trend lies in a continuing increase in leakage power dissipation, which now accounts for an increasingly large share of processor power dissipation. This is especially the case for large on-chip SRAM memories. A large fraction of processor area is devoted to the SRAM memories, mainly L1 and L2 caches. For instance, 60% of Manuscript

Indoor localization system is one of many trendy services that fall within the framework of Smart Buildings and Internet of Things development. The Wireless Sensor Networks (WSN) technology has tremendously contributed to this field of research especially in the development of low cost solutions. The wireless nodes in the indoor localization platforms are becoming battery-powered to overcome the high costs of wired power supply and to maintain high installation flexibility in dynamic indoor environments. Since the battery has a limited energy capacity, it is important to find methods to optimize the power consumption within the sensor node. To increase the battery lifetime, the wireless node must be maintained as long as possible at its lowest power consumption level which is called sleep mode. This article presents an energy-efficient on-demand protocol for the WSN-based indoor localization platform. In this protocol the wireless nodes are maintained in low power idle listening mode using low power built-in Wake-Up receiver and they are activated only when a localization request occurs.

Because of the fact that users can connect to a WiMAX (IEEE 802.16) network wirelessly with large-scale movement capability, it is inevitable that they cannot access electrical power sources at their desired time. As a result, a mechanism is needed to reduce power consumption; and therefore three power saving classes have been defined in WiMAX that each one is designed for a specific application. Although using a suitable power saving class (PSC) can reduce power consumption significantly, but lack of cross-layer coordination can reduce the efficiency of the power saving mechanism. Since real-time services which are related to power saving class type II (PSC II) have great importance and vast applications, an improved PSC II algorithm for WiMAX is proposed in this paper which not only guarantees WiMAX quality of service (QoS), but also makes the cross-layer coordination using a proactive buffer resulting in less power consumption. There is also a comparison made between the performance of the proposed algorithm and the predefined PSC II algorithm in WiMAX using computer simulations and it shows that using the proposed algorithm reduces power consumption by 60 percent, while WiMAX QoS is still guaranteed.

Recent studies show that peripheral circuit (including decoders, wordline drivers, input and output drivers) constitutes a large portion of the cache leakage. In addition, as technology migrates to smaller geometries, leakage contribution to total power consumption increases faster than dynamic power, indicating that leakage will be a major contributor to overall power consumption. This paper presents zig-zag share, a circuit technique to reduce leakage in SRAM peripherals by putting them into low-leakage power sleep mode. The zig-zag share circuit is further extended to enable multiple sleep modes for cache peripherals. Each mode represents a trade-off between leakage reduction and the wakeup delay. Using architectural control of multiple sleep modes, an integrated technique called MSleep-Share is proposed and applied in L1 and L2 caches. MSleep-share relies on cache miss information to guide leakage control mechanism and switch peripheral circuit's power mode. The results show leakage reduction by up to 40 in deeply pipelined SRAM peripheral circuits, with small area overhead and small additional delay. This noticeable leakage reduction translates to up to 85% overall leakage reduction in on-chip memories. Index Terms-Horizontal and vertical sleep transistor sharing, leakage power, multiple sleep modes, SRAM peripheral. C MOS technology scaling has been a primary driving force to increase the processor performance. A drawback of this trend lies in a continuing increase in leakage power dissipation, which now accounts for an increasingly large share of processor power dissipation. This is especially the case for large on-chip SRAM memories. A large fraction of processor area is devoted to the SRAM memories, mainly L1 and L2 caches. For instance, 60% of Manuscript

Because of their pervasiveness and autonomy in operation, mesh-based wireless sensor networks (WSNs) are an ideal candidate in offering sustained monitoring functions at reasonable cost over a wide area. However, devising an energy-efficient, cost-effective, and reliable communication strategy for WSNs requires tight collaboration of all of the sublayers, which introduces new technical challenges in the areas of data, network and power management. This paper proposes a cross-layer sleep scheduling-based organizational approach, called Sense-Sleep Trees (SS-Trees), that aims to harmonize the various engineering issues and provides a method of increasing monitoring coverage and operational lifetime of mesh-based WSNs engaged in wide-area surveillance applications. An iterative algorithmic approach is suggested to determine the feasible SS-Tree structures to achieve such design goals. Based on the computed SS-Trees, optimal sleep schedules and traffic engineering measures can be devised to balance sensing requirements, network communication constraints, and energy efficiency. For channel access, a simple single-channel CSMA MAC with implicit acknowledgements (IACKs) is selected to complement SS-Tree implementation because of its flexibility and adaptability in face of the unique operational characteristics of WSNs.

Mobile platforms, such as laptops, tablets or Ultrabooks, must feature always-on network connectivity to make mobile applications (e.g., email, instant messaging, etc.) visible and accessible to/from the Internet. Always-on connectivity for mobile platforms can be achieved conventionally by periodically exchanging keep-alive messages with their counterparts (i.e., servers). However, frequent message exchange wastes energy because it requires the platform to operate in (or transition to) the active state (e.g., S0) instead of remaining in a long, uninterrupted low-power standby mode. To address this problem, we present a novel and secure, yet simple, architecture, called Energy Efficient Always-On-Connectivity (EE-AOC), that allows mobile devices/applications to be continuously visible and reachable from the network. EE-AOC offloads the keep-alive message exchange process to the network device from the host, thus, it does not need to wake up the whole platform. Our experimental results implementing the prototype show that EE-AOC achieves always-on connectivity and application reachability at about 85% lower power (i.e. 6.67X gain) than that needed to provide the same functionalities in today's platforms.

Wireless telecommunication networks have become fundamental to our daily activities. Today, people have access to at least one type of wireless telecommunication network with Mobile Stations (MS) supporting multiple applications that consume more battery power; as well as a constant increase in multimedia applications that possess a critical challenge in efficient battery management. MSs are battery powered devices with limited lifetime. An efficient management of the battery will extend its lifetime before recharging exercise is conducted. World Wide Interoperability for Microwave Access (WiMAX), is design to Supports Higher Bandwidth with different traffic classes support for Power Management. Due to the mobility Characteristics introduced in WiMAX, power savings became an important problem; Since MS has limited superimpose life that requires recharging exercise when the battery life is depleted. Thus, Battery Lifetime Aware Power Saving Scheme (BLAPS) and an Adaptive Power Saving Scheme were proposed to extend the Battery Life, but the first scheme resulted in frequent transition to listening mode which led to waste of energy. While the former has higher energy consumption resulting to poor QoS that degrades the overall performance of MS. Hence, a Quality of Service (QoS) Aware Power Saving Scheme is proposed to improve the QoS. The scheme introduced a Modified minimum (Tmin) and Maximum (Tmax) sleep intervals in order to enhance the parameters of the variant schemes. In addition, the scheme also introduced a modified sleep window as well as QoS Aware algorithm that enable the adjustments of the sleep Parameters more appropriately in order to minimize frequent Transition to listening mode while improving efficiency. Finally, a state transition diagram was also developed. The proposed scheme was evaluated using MATLAB simulator; the results proved that the proposed QoS Aware Scheme has superior performance in terms of consumption rate and response delay respectively.

Monitoring some sites using a wireless sensor network (WSN) may be hampered by the difficulty of recharging or renewing the batteries of the sensing devices. Mechanisms aiming at improving the energy usage at any moment while fulfilling the application requirements are thus key for maximizing the lifetime of such networks. Among the different methods for achieving such a goal, we focus on energy management methods based on duty-cycling allowing the sensors to switch between two modes: a high-energy mode (active) and a lowenergy mode (sleep). In this paper we propose two new scheduling heuristics for addressing the problem of maximizing the lifetime of a WSN under the constraint of coverage of a subset of fixed targets. The first one is a stochastic greedy algorithm and the second one is based on applying Simulated Annealing (SA). Both heuristics use a specific knowledge about the problem. Experimental results show that while both algorithms perform well, greedy algorithm is preferable for small and medium sizes networks, and SA algorithm has competitive advantages for larger networks.

To my father, who would have been silently proud. Résumé en Langue Française Que le phénomène découle d'une prise de conscience des conséquences sur l'environnement, d'une opportunité économique ou d'une question de réputation et de commerce, la réduction des émissions de gaz à effets de serre est récemment devenue un objectif de premier plan. Les individus, les entreprises et les gouvernements effectuent un effort important pour réduire la dépense énergétique de multiples secteurs d'activité. Parallèlement, les technologies de l'information et de la communication sont de plus en plus présentes dans la plupart des activités humaines et l'on a estimé que 2 % des émissions de gaz à effets de serre pouvaient leur être attribuées, cette proportion atteignant 10 % dans les pays fortement industrialisés [1, 2]. Si ces chiffres paraissent raisonnables aujourd'hui, ils sont certainement appelés à croître à l'avenir. À l'heure du cloud computing, les infrastructures de calcul et de communication demandent de plus en plus de performance et de disponibilité et imposent l'utilisation de matériels puissants et engendrant une consommation d'énergie importante du fait de leur fonctionnement direct, mais aussi à cause du refroidissement qu'ils nécessitent. En outre, les contraintes de disponibilité imposent une conception d'architectures redondantes et dimensionnées sur une charge crête. Les infrastructures sont donc souvent sous-utilisées et adapter leur niveau de performance à la charge effectivement constatée constitue une piste d'optimisation prometteuse à divers niveaux. Si l'on adopte un strict point de vue environnemental, l'objectif du Green Networking consiste à réduire le volume d'émissions de gaz à effets de serre dues au processus de communication. L'utilisation de sources d'énergie renouvelables ou d'électronique de faible consommation (par exemple asynchrone) constituent des pistes évidentes d'amélioration. Il existe en outre de nombreuses stratégies d'optimisation liées à la conception physique de l'infrastructure elle même. Il est par exemple possible de localiser les éléments consommateurs en énergie (centres de calcul, etc.) proche des points de production afin d'éviter les pertes liées au transport de l'énergie sur de longues distance. Il est aussi possible de privilégier les endroits dans lesquels la température extérieure est faible tout au long de l'année afin de limiter l'utilisation de climatisation au profit d'une simple ventilation. Ces stratégies peuvent avoir un impact important sur la consommation effective de l'infrastructure mais n'interviennent qu'en moindre mesure sur les aspects réseaux. La délocalisation d'éléments consommateurs, par exemple, impose des contraintes à V Les scénarios de référence Pour certifier la performance des algorithmes proposés, nous profitons des profils de trafic mesurés, et des scénarios de réseau réels, représentant des réseaux de recherche internationaux, ou des réseaux de fournisseur d'accès à Internet, fournis par les fournisseurs d'accès Internet eux-mêmes. En outre, nous certifions la performance des solutions sur une gamme de scénarios de réseau, représentant un jeu hétérogène que couvre les réseaux d'extensions différentes et les différents niveaux hiérarchiques: réseaux d'acces, réseaux métro, jusqu'à réseaux de backbone. Les quatre scénarios de référence principaux, évalués pour les différentes solutions étudiées dans le travail de thèse, sont reportés dans Figure 5. Ils représentent (i) Un réseau de recherche européen (GEANT [13]), (ii) le segment de backbone d'un réseau de fournisseur d'accès Internet européen (France Télécom), (iii) le segment de métro d'un fournisseur d'accès Internet national européen, et (iv) le réseau national d'un fournisseur d'accès Internet européen. Aussi en ce qui concerne les profils de consommation énergétique de dispositifs de réseau, nous avons utilisé des chiffres mesurés et des profils d'énergie largement acceptés dans la littérature, en attestant, aussi, la sensibilité des résultats aux variations de tels modèles d'énergie, en représentant d'éventuelles évolutions dans les technologies de réseau. Conclusions et Directions des Travaux Futures Dans ce travail de thèse, nous avons étudié des solutions pour pousser la conscience d'énergie dans les réseaux câblés, d'après le principe de consolidation de ressource. Ces dernières années, la question de rendement énergétique est arrivée à l'importance primordiale tant pour les industries que pour la communauté de recherche, à cause de ses implications économiques potentielles et de son impact attendu sur l'environnement. Dans ce contexte, bien que le domaine de réseau vert soit toujours à ses débuts, un certain nombre de travaux intéressants ont déjà été effectués, explorant des directions de recherche différentes. En particulier nous avons principalement fait levier sur le paradigme de routage avec conscience d'énergie, en proposant et en analysant des solutions techniques tant centralisées que distribuées. Contributions Notre premier travail vers le "greening" de réseaux a visé à déterminer les différents paradigmes actuellement explorés pour réduire les dépenses énergétiques de réseau et ceux qui peut toujours être exploré. Pour chaque paradigme, nous dessinons l'état de l'art et soulignons les points qui ont besoin de plus recherche. Nous avons proposé une taxonomie des travaux pertinente dans la gestion des réseaux verts. Notre contribution principale au domaine des réseaux verts concerne le routage avec conscience Résumé en Langue Française V Contents XIX List of Figures XXI List of Tables XXIII Abbreviations XXV

The energy consumption of network devices, and, as a consequence, of communication networks, is generally independent from their level of utilization, which results in a waste of energy when the network is lightly loaded. Ideally the consumption of a network should be proportional to the amount of traffic it conveys. The most straightforward way to enforce such a proportionality between the network energy consumption and its utilization level, is to dynamically adapt the status of network devices to the load, forcing a subset of them to enter a sleep state during the low activity periods. We present in this paper an algorithm to dynamically put links into a sleep state, based on a cooperative-game approach, named "L-Game". Our approach decides which links can be switched off based on a measure of the criticality of each link expressed as its Shapley value. This measure combines topological aspects and traffic conditions. Simulation results on real network scenarios show that our solution achieves a better trade off between energy saving and Traffic Engineering than other legacy approaches.

We propose a novel distributed approach to exploit sleep mode capabilities of links in an Internet Service Provider network. Differently from other works, neither a central controller, nor the knowledge of the current traffic matrix is assumed, favoring a major step towards making sleep mode enabled networks practical in the current Internet architecture. Our algorithms are able to automatically adapt the state of network links to the actual traffic in the network. Moreover, the required input parameters are intuitive and easy to set. Extensive simulations that consider a real network and traffic demand prove that our algorithms are able to follow the daily variation of traffic, reducing energy consumption up to 70% during off peak time, with little overheads and while guaranteeing Quality of Service constraints.

In this work, we face the problem of reducing the power consumption of Internet backbone networks. We propose a novel algorithm, called GRiDA, to selectively switch off links in an Internet Service Provider IP-based network to reduce the system energy consumption. Differently from approaches that have been proposed in the literature, our solution is completely distributed and thus not requiring any centralized oracle. It leverages link-state protocol like OSPF to share a limited amount of information, and to reduce the problem complexity. Another key feature of GRiDA is that it does not require the knowledge of the actual and past/future traffic matrices, being able to run in real-time, where this information would not be available. Results, obtained on realistic case studies, show that GRiDA achieves performance comparable to several existing centralized algorithms, guaranteeing energy savings up to 50%.

Energy is a major expense issue for mobile operators. In the case of wireless networks, base stations have been identified as the main source of energy consumption. In this paper, we study the energy consumption reduction problem based on real measurements for a commercial multi-band LTE network. Specifically, we are interested in sleep modes to turn off certain frequency bands during low traffic periods and consequently reduce power consumption. We determine the number of frequency bands really needed at each time period. The frequency bands that are not needed can be disabled to reduce energy consumption. In order to allow the operator to predict how many bands can be switched off without major impact on the quality of service, we propose to use a deep learning algorithm, such as Long-Short Term Memory (LSTM). Based on the captured data traces, we have shown that the proposed LSTM model can save an average of 8% to 21% of the energy consumption during working days.

In Sensor-MAC (S-MAC) protocol, a node located between two or more virtual clusters is called boarder node that adopts different listen and sleep schedules. These border nodes consume a large amount of energy as they switch to the listening mode often due to diversified scheduling which in turns decreases the lifetime of the wireless sensor network. This paper proposed a new unified scheduling method to solve the diversified scheduling problem of border nodes in S-MAC and evaluated the performance through simulation. It has been observed from the simulated results that the border nodes have consumed less power in case of large network as well as small networks.

The current revolution in communication and information technology is facilitating the Internet of Things (IoT) infrastructure. Wireless Sensor Networks (WSN) are a broad category of IoT applications. However, power management in WSN poses a significant challenge when the WSN is required to operate for a long duration without the presence of a consistent power source. In this paper, we develop a batteryless, ultra-low-power Wireless Sensor Transmission Unit (WSTx) depending on the solar-energy harvester and LoRa technology. We investigate the feasibility of harvesting ambient indoor light using polycrystalline photovoltaic (PV) cells with a maximum power of 1.4mW. The study provides comprehensive power management design details and a description of the anticipated challenges. The power consumption of the developed WSTx was 21.09µW during the sleep mode and 11.1mW during the operation mode. The harvesting system can harvest energy up to 1.2mW per second, where the harvested energy ca...

Energy consumption strategy is crucial to the future of Broadband Wireless Access (BWA). In order to manage limited battery power efficiently, the IEEE 802.16e standard defines the sleep mode operation in its MAC protocol to maximize the lifetime of Mobile Station (MS) and to enhance the network capability. In this paper, we analytically investigate the power consumption of listening state and sleep state operations of IEEE 802.16e. A Mobile Station goes to sleep mode when there is no data to send or receive with the Base station (BS). After a Mobile Station stays in sleep state for a pre-defined time, it wakes up and transits to listening state periodically to check if the Base Station has any buffered downlink traffic destined to the Mobile Station itself. Although the listening interval is shorter than sleep interval, the power consumption should consider both listening state and sleep state operations. Our proposed model and numerical results prove the listening state may consum...

In this paper, we propose an energy-efficient small cell operation algorithm for ultra-dense cellular networks to improve the energy efficiency of the networks. To that end, the algorithm generates a dataset consisting of the location information of inactive small cells and static UEs. For an overload condition in a macro cell, the algorithm performs clustering with the density-based spatial clustering of applications with noise to find clusters with small cells. Therefore, based on conditions a target cluster is selected and the small cells in the cluster are switched to the active mode in order to share loads from the macro cell. For an under-load scenario in the macro cell, the algorithm finds a small cell with the lowest radio load and conditionally switches the cell to sleep mode. Through systemlevel simulations, the performance of the proposed algorithm is evaluated. The simulation results showed that the proposed approach can ensure a higher energy efficiency than previous al...

In this paper, we propose an energy-efficient small cell operation algorithm for ultra-dense cellular networks to improve the energy efficiency of the networks. To that end, the algorithm generates a dataset consisting of the location information of inactive small cells and static UEs. For an overload condition in a macro cell, the algorithm performs clustering with the density-based spatial clustering of applications with noise to find clusters with small cells. Therefore, based on conditions a target cluster is selected and the small cells in the cluster are switched to the active mode in order to share loads from the macro cell. For an under-load scenario in the macro cell, the algorithm finds a small cell with the lowest radio load and conditionally switches the cell to sleep mode. Through systemlevel simulations, the performance of the proposed algorithm is evaluated. The simulation results showed that the proposed approach can ensure a higher energy efficiency than previous al...

Energy consumption is one of the most important challenges in Millimeter Wave (mmWave) 5G wireless communications since higher data rate and lower latency are required. Thus, User Equipment (UE) battery suffers from its energy absorption. To investigate a green communication, Discontinuous Reception (DRX) mode is introduced when no traffic arrival from the Base Station (BS) to extend UE battery lifetime but delay is increased. This paper introduces an advanced DRX, which can achieve extended UE battery lifetime with a reasonable reduced delay due to a proposed sub-frame size. Generally, traffic which arrives may be data packet or paging message. This paper evaluates two proposed system models based on traffic which arrives during wake up periods of the UE. The first system model is called Signaling Based DRX and the second system model is called Enhanced Paging Monitoring (EPM). The both system models utilize two different indicators; they are Power Saving Indicator (PSI) and Paging Early Indicator (PEI), respectively. These indicators enhance power saving and delay compared to that of the traditional approach. The evaluation of the both system models performance is by measuring the power saving factor and the average delay of the UE over the same data/paging traffic arrival rate. A MATLAB simulation program is used to validate the system model and the numerical analysis. Analytical and numerical results are considered.

The increased number of cellular network subscribers is giving rise to the network densification in next generation networks further increasing the greenhouse gas emission and the operational cost of network. Such issues have ignited a keen interest in the deployment of energy-efficient communication technologies rather than modifying the infrastructure of cellular networks. In cellular network largest portion of the power is consumed at the Base stations (BSs). Hence application of energy saving techniques at the BS will help reduce the power consumption of the cellular network further enhancing the energy efficiency (EE) of the network. As a result, BS sleep/wake-up techniques may significantly enhance cellular networks' energy efficiency. In the proposed work traffic and interference aware BS sleeping technique is proposed with an aim of reducing the power consumption of network while offering the desired Quality of Service (QoS) to the users. To implement the BS sleep modes in an efficient manner the prediction of network traffic load is carried out for future time slots. The Long Short term Memory model is used for prediction of network traffic load. Simulation results show that the proposed system provides significant reduction in power consumption as compared with the existing techniques while assuring the QoS requirements. With the proposed system the power saving is enhanced by approximately 2% when compared with the existing techniques. His proposed system will help in establishing green communication networks with reduced energy and power consumption.

Wireless sensor networks proliferate more and more in all social scopes and sectors. Such networks are implemented in smart homes, smart cities, security systems, medical resources, agriculture, automotive industry, etc. Communication devices and sensors of such networks are powered with batteries: the enlarging of battery life is a hot research topic. We focus on wireless sensor networks based on ZigBee technology. While sleep standard operation mode is defined for end devices, it is not the case for the rest of devices (routers and Coordinator), which usually always remain in active mode. We designed a formal optimization model for maximizing the enlarging of the battery life of routers and Coordinator, allowing us to delimit practical successful conditions. It was successfully tested with a standard ZigBee datasheet comprising technical data for sensors, routers, and coordinators. It was tested in a practical wireless sensor network assembly with XBee S2C devices. We derived, fro...

A wireless sensor network (WSN) is a wireless network consisting of distributed autonomous devices using sensors to observe physical or environmental conditions. The energy consumption is very important for WSNs. The paper presents that measurement of the energy consumption of indoor environment. Ti CC2538 modules were used as WSN nodes and they were programmed via Contiki Operating System (OS). Simulator of Contiki OS is COOJA. The program was simulated with COOJA before being tried in real life. Then, measurements were taken directly from the module via Labview and DAQ card. The network used Low Energy Adaptive Clustering Hierarchy (Leach) protocol which is a very popular networking protocol for WSN. The nodes in the network were prevented to go in sleep mode. Therefore, measurements showed transmit and receive mode energy consumption. On the other hand, cluster head election period and transmission period of sensed data selected as short as possible to make measurements in a short time. The proposed measurement system can be used evaluate any new networking protocol more realistically.

An ad-hoc network is a group of mobile wireless nodes that cooperatively form a network among themselves without any fixed infrastructure. Each node in ad-hoc network forward packets for other nodes to allow nodes not within direct wireless transmission range to communicate. There has been considerable research on conserving power in the routing protocol. Although most of these researches focused on controlling the transmission power of the sender network interface. Increasing power consumption and packet storming within ad-hoc network is becoming a core issue for these low power mobile devices. This work focuses on an approach for energy conservation as well as reducing packet storming within the routing protocol of the ad-hoc network. A wireless network interface in sleep mode consumes less power than idle mode. In this work we propose an improvement on DSDV protocol to allow sleep mode to take part in communication of the ad-hoc network.

Energy consumption strategy is crucial to the future of Broadband Wireless Access (BWA). In order to manage limited battery power efficiently, the IEEE 802.16e standard defines the sleep mode operation in its MAC protocol to maximize the lifetime of Mobile Station (MS) and to enhance the network capability. In this paper, we analytically investigate the power consumption of listening state and sleep state operations of IEEE 802.16e. A Mobile Station goes to sleep mode when there is no data to send or receive with the Base station (BS). After a Mobile Station stays in sleep state for a pre-defined time, it wakes up and transits to listening state periodically to check if the Base Station has any buffered downlink traffic destined to the Mobile Station itself. Although the listening interval is shorter than sleep interval, the power consumption should consider both listening state and sleep state operations. Our proposed model and numerical results prove the listening state may consume up to 90% of the total power consumption in some case.

This work presents a novel circuit for detecting transient faults in combinational and sequential logic. The detection mechanism features a built-in current sensor connected to the bulks of the monitored logic. The proposed circuit was optimized in terms of power consumption and enhanced with low-power sleep-mode. In addition, a calibration method for bulk built-in current sensors is presented. Overhead results indicate an increase of only 15% in power consumption which represents an improvement of factor 7 compared to similar existing sensors. .

The use of wireless sensor networks (WSNs) in modern precision agriculture to monitor climate conditions and to provide agriculturalists with a considerable amount of useful information is currently being widely considered. However, WSNs exhibit several limitations when deployed in real-world applications. One of the challenges faced by WSNs is prolonging the life of sensor nodes. This challenge is the primary motivation for this work, in which we aim to further minimize the energy consumption of a wireless agriculture system (WAS), which includes air temperature, air humidity, and soil moisture. Two power reduction schemes are proposed to decrease the power consumption of the sensor and router nodes. First, a sleep/wake scheme based on duty cycling is presented. Second, the sleep/wake scheme is merged with redundant data about soil moisture, thereby resulting in a new algorithm called sleep/wake on redundant data (). can minimize the power consumption and data communication of the ...

In recent times, aerial base stations(AeBSs) are being investigated to provide wireless coverage to terrestrial radio terminals. The advantages of using aerial platforms to provide wireless coverage are many including larger coverage in remote areas, better line-of-sight conditions etc. Energy is a scarce resource for aerial base stations, hence the wise management of energy is quite beneficial for the aerial network. In this context, we study the means of reducing the total energy consumption by designing and implementing an energy efficient aerial base station as presented in this paper. Sleep mode implementation in base stations (BSs) has proven to be a very good approach for improving the energy efficiency and in this paper we propose a novel strategy for further improving energy efficiency by considering ternary state transceivers for an AeBSs. Using the three state model, we propose a Markovian Decision process (MDP) based algorithm, which intelligently switches between the states of the transceivers based on the offered traffic whilst maintaining a prescribed minimum channel rate per user. We have defined a reward function for the MDP, which helps us to get an optimal policy for selecting a particular mode for the transceivers of the AeBS. Considering an aerial BS with state changeable transceivers, we perform simulations to analyse the performance of the algorithm. Our results show that, around 40% gain in the energy efficiency is achieved while using our proposed MDP algorithm together with the three-state transceiver model compared to the always active mode. We also show the energy-delay tradeoff in order to design an efficient aerial base station.

Active geometry induced mechanical stress is optimized for minimum variation of CMOS electrical characteristics with varying active profiles. Wafers with two different STI stress levels were manufactured for this study. By co-optimizing STI stress and the active profile of model test structures, less than 3% device deviation was achieved in comparison to SPICE model across the full breadth of N/PMOS geometry.

In this paper, we present a design and an evaluation of two power management modes that reduce the energy consumption of OpenFlow switches. First, we define two new low power modes: SLEEP PORT and SLEEP SWITCH, which reduce energy consumption in cases where packets on port or switches are absent. Second, we present a Wake on LAN (WOL) method for OpenFlow Switches to wake up Ethernet ports or the whole switch from inactive states. Finally, we describe our design, experimental results and performance evaluations. Our results show that the control SLEEP PORT mode on a switch might save about 9.8% power consumption per port, and up to about 60% of total power consumption of the switch with SLEEP SWITCH mode. In addition, we will implement this method to Openflow Switch bases on NetFPGA-10 Gigabit in the future.

Multi-hop wireless sensor networks are mainly designed for environment monitoring. The lifetime of networks depends on the durability of the battery resource sensors, so it is crucial for sensors to efficiently use limited battery resource. The energy expends by sensor nodes in communication makes-up a quantum of their total amount of energy consumption. In existing research, most of the energy-saving MAC protocols reduce energy consumption by putting periodically sensors to sleep mode. Such a regular active/sleep schedule fails to adjust individual sensor node sleep duration according to persensor node communication traffic loads, which causes unnecessary idle listening problem and low power-efficiency. In this paper, we present an efficient energy-saving MAC protocol for saving energy in a multi-hop wireless sensor networks. This proposed protocol dynamically adjusts the active/sleep time duration of each sensor according to persensor node communication traffic load. Meanwhile, it can lead to much greater energy-efficiency by prolonging the sensor nodes sleeping duration, when in a network at persensor node communication traffic load is low. The basic idea of this proposed protocol is an analytical model for estimating the accurate per-sensor node communication traffic load in a multi-hop wireless sensor network and a grid-based quorum concept for regular active/sleep schedule.

Multi-hop wireless sensor networks are mainly designed for environment monitoring. The lifetime of networks depends on the durability of the battery resource sensors, so it is crucial for sensors to efficiently use limited battery resource. The energy expends by sensor nodes in communication makes-up a quantum of their total amount of energy consumption. In existing research, most of the energy-saving MAC protocols reduce energy consumption by putting periodically sensors to sleep mode. Such a regular active/sleep schedule fails to adjust individual sensor node sleep duration according to persensor node communication traffic loads, which causes unnecessary idle listening problem and low power-efficiency. In this paper, we present an efficient energy-saving MAC protocol for saving energy in a multi-hop wireless sensor networks. This proposed protocol dynamically adjusts the active/sleep time duration of each sensor according to persensor node communication traffic load. Meanwhile, it can lead to much greater energy-efficiency by prolonging the sensor nodes sleeping duration, when in a network at persensor node communication traffic load is low. The basic idea of this proposed protocol is an analytical model for estimating the accurate per-sensor node communication traffic load in a multi-hop wireless sensor network and a grid-based quorum concept for regular active/sleep schedule.

The Internet of Things (IoT) refers to electronic device communications, one of them is the wireless sensor network (WSN). Battery life is the main challenge for WSN. Battery life refers to the maximum time until one node not work. This article presents the prototype design and testing of a selfpowered IoT devices for use in precision agriculture. This study proposed to increase the battery life of WSN by applying solar energy harvesting technology. The system consists of several nodes equipped with solar cell and energy harvester. The system uses sleep mode with certain active intervals to save power. The custom multi-hop protocol provides energy efficient communication from any device in a wireless sensor network. The sensor data is transmitted to a gateway, which then forwards it to a local server or cloud service, where the data can be analyzed to optimize the production in agriculture. The preferred topologies and protocols in multi-hop WSNs have a significant impact on energy consumption. In this paper, experimental validation of the self-powered WSN for indoor monitoring proposed on multi-hop topology. The choice of solar cell type, microcontroller, and sensor are the main factors for device development. The harvested energy must be above the WSN energy requirements.