Authentication of Real-Time Communication System Using KIS Scheme
EMC/HumanCom, 2013
In global communication environment, signature computation will be frequently performed on a rela... more In global communication environment, signature computation will be frequently performed on a relatively insecure device that cannot be trusted all times to maintain the secrecy of the private key. To deal with this, Dodis et al. [1] proposed a strong key-insulated signature schemes whose goal is to minimize the damage caused by secret-key exposures. This environment will become more important when we focus on real time communication like telephony, TV shopping, electronic voting etc. Any flaws in the authentication system cause a critical damage to the real time environment. Considering this scenario we proposed a KIS scheme based on elliptic curve cryptography, which minimizes the damage of key exposer. Its security is based on elliptic curve discrete logarithm problem (ECDLP) assumption, and efficient in terms of computational cost and signature size.
With the dynamic demands and stringent requirements of various applications, networks need to be ... more With the dynamic demands and stringent requirements of various applications, networks need to be highperformance, scalable, and adaptive to changes. Researchers and industries view network softwarization as the best enabler for the evolution of networking to tackle current and prospective challenges. Network softwarization must provide programmability and flexibility to network infrastructures and allow agile management, along with higher control for operators. While satisfying the demands and requirements of network services, energy cannot be overlooked, considering the effects on the sustainability of the environment and business. This paper discusses energy efficiency in modern and future networks with three network softwarization technologies: SDN, NFV, and NS, introduced in an energy-oriented context. With that framework in mind, we review the literature based on network scenarios, control/MANO layers, and energy-efficiency strategies. Following that, we compare the references regarding approach, evaluation method, criterion, and metric attributes to demonstrate the state-of-the-art. Last, we analyze the classified literature, summarize lessons learned, and present ten essential concerns to open discussions about future research opportunities on energy-efficient softwarized networks.
IEEE Transactions on Vehicular Technology, Dec 1, 2021
Due to the fact that most user equipments (UEs) do not have enough computation power, time-sensit... more Due to the fact that most user equipments (UEs) do not have enough computation power, time-sensitive tasks should be offloaded to other computation resources. In such cases, a cloud is an ideal destination to which computation tasks can be offloaded because of its huge data processing power. However, the distance between a UE and the cloud may increase the latency of data transmission. At the same time, edges and vehicular-fogs (consisting of electric vehicles with computing resources) are closer to UEs and mostly remain under-utilized. To address this issue, a federated architecture with UEs, vehicular-fogs (parking lot fog and traffic intersection fog), edges, and cloud is proposed along with a probabilistic offloading strategy. The quality of service (QoS) violation probability can be minimized by finding the optimal offloading probabilities while satisfying the delay constraint through an optimal offloading probability estimation algorithm based on the subgradient method proposed in this paper. Our results show that the QoS violation probability and the average waiting time can be decreased by 10%-12% and 45%, respectively, for a federated architecture with two vehicular-fogs as compared to an architecture without any fogs. As offloading to edges and cloud has longer communication delays than offloading to vehicular-fogs, the offloading probabilities to the edges in the architecture with two vehicular-fogs in the case of heavy traffic are reduced by nearly 35% as compared to the architecture without any fogs.
Telecommunication carriers of 5G-MEC are re-architecting their central offices and mobile base st... more Telecommunication carriers of 5G-MEC are re-architecting their central offices and mobile base stations as datacenters with network function virtualization (NFV) technology. These datacenters (DCs) are known as edge datacenters that help network operators speed deployment and reduce costs. Previously, the use of NFV was limited to within a datacenter (DC) known as intra-DC. Recently, many studies have been conducted into the use of NFV across DCs, i.e., inter-DC. However, these NFV inter-DC architectures have limited communication between DCs with either horizontal or vertical connectivity. In this paper, we propose a generic architecture of such edge NFV datacenters with both horizontal and vertical connectivity, and demonstrate the consequences of both vertical and horizontal connectivity between DCs in terms of communication and computing costs. We formulate a cost optimization problem with latency and capacity as constraints by estimating the traffic dispatch rate between DCs. We propose a vertical-horizontal communication (VHC) heuristic solution to the NP-hard problem. Compared to horizontal connectivity, our results show that vertical connectivity helps to reduce computing costs by 10-30%. However, both vertical and horizontal communications together can help to reduce such costs by 20-30% compared to only vertical communication. INDEX TERMS Inter-DC connectivity, VNF placement, service chaining, communication, computing. BINAYAK KAR (Member, IEEE) received the Ph.D. degree in computer science and information engineering from National Central University
The federation between cloud and edge has been proposed to exploit the advantages of both technol... more The federation between cloud and edge has been proposed to exploit the advantages of both technologies. However, the existing studies have only considered cloud-edge computing systems which merely support vertical offloading from edges to clouds in one direction. However, there are certain cases, where the offloading needs to be done from clouds to edges and between edges. Such a cloud to edge offloading is called reverse offloading. To this end, this paper proposes a generic Omni-directional architecture of cloud-edge computing systems intending to provide vertical and horizontal offloading. To investigate the effectiveness of the proposed architecture in different operational scenarios, we formulate the dual cost optimization problem with different latency (loose, low, ultra-low) constraints. We develop an offloading algorithm using simulated annealing (SA). The experimental results show by our proposed OMNI architecture we can reduce the total cost by 15-25% and 10-20% in non-uniform and uniform inputs, respectively, compared to other existing architectures. The average latency in OMNI architecture is relatively very less compared to other architectures. It also increases utilization in the edge nodes by 5-30% in comparison to other existing architectures.
Vehicular-fog system consists of vehicles with computing resources that are mostly under-utilized... more Vehicular-fog system consists of vehicles with computing resources that are mostly under-utilized. Therefore, an edge system may offload some workloads for remote execution at nearby vehicular-fogs. Whether this is cost-effective depends on not only the costs and computation capacities of vehicles but also the amount of workloads and associated latency constraint. In this paper, we consider a two-tier federated Edge and Vehicular-Fog (EVF) architecture and aim to minimize overall cost while meeting latency constraint by setting up an appropriate offloading configuration. We model this to a singleobjective mixed integer programming problem. To solve this mixed integer problem in real time we propose an iterative greedy algorithm using the queuing model. The results show, our proposed architecture reduces the cost of vehicular-fogs by 40-45% and the total cost by 35-40% compared to the existing architecture and help the edge to provide services beyond its capacity with specified latency constraint.
The huge amount of data generated by the Internet of things (IoT) devices needs the computational... more The huge amount of data generated by the Internet of things (IoT) devices needs the computational power and storage capacity provided by cloud, edge, and fog computing paradigms. Each of these computing paradigms has its own pros and cons. Cloud computing provides enhanced data storage and computing power but causes high communication latency. Edge and fog computing provide similar services with lower latency but with limited capacity, capability, and coverage. A single computing paradigm cannot fulfil all the requirements of IoT devices and a federation between them is needed to extend their capacity, capability, and services. This federation is beneficial to both subscribers and providers and also reveals research issues in traffic offloading between clouds, edges, and fogs. Optimization has traditionally been used to solve the problem of traffic offloading. However, in such a complex federated system, traditional optimization cannot keep up with the strict latency requirements of decision making, ranging from milliseconds to sub-seconds. Machine learning approaches, especially reinforcement learning, are consequently becoming popular because they can quickly solve offloading problems in dynamic environments with large amounts of unknown information. This study provides a novel federal classification between cloud, edge, and fog and presents a comprehensive research roadmap on offloading for different federated scenarios. We survey the relevant literature on the various optimization approaches used to solve this offloading problem, and compare their salient features. We then provide a comprehensive survey on offloading in federated systems with machine learning approaches and the lessons learned as a result of these surveys. Finally, we outline several directions for future research and challenges that have to be faced in order to achieve such a federation.
International journal of computer and communication technology, Apr 1, 2012
Blind signature allows one user to get a signature without giving the signer any information abou... more Blind signature allows one user to get a signature without giving the signer any information about the actual message or the resulting signature. In this paper, we aim to improve the recently proposed Lin et al.'s Self-certified Partially Blind Signature Scheme[1] in order to withstand the security flaw in their scheme. The security of the improved scheme is enhanced in the blind signing phase of the scheme. The analysis shows that the proposed scheme resolves security problem in Lin et al.'s scheme and also meets the aspects of security features needed by a partial blind signature.
IEEE Transactions on Network and Service Management, Sep 1, 2016
Due to the large installed base of distributed legacy networks, software defined networking (SDN)... more Due to the large installed base of distributed legacy networks, software defined networking (SDN) nodes may be required to coexist with legacy nodes to form hybrid networks. It has been shown that such a hybrid network has better performance than a pure legacy network due to smarter transmission scheduling. Despite such advantages, limited budgets continue to hinder the rapid adaptation of SDNs. Only a part of the network can be upgraded at a time especially for large-scale networks. In this paper, we define the minimum percentage of SDN nodes in a path, and paths with at least one SDN node, as the hop coverage and path coverage, respectively. We intend to evaluate the relationship between cost and coverage in the partially deployed SDNs. We formulate SDN node selection as four optimization problems with hop/path coverage and cost as objectives and constraints, respectively, and vice-versa. We propose two heuristic solutions: 1) maximum number of uncovered path first (MUcPF) and 2) maximum number of minimum hop covered path first (MMHcPF), to these NP-hard problems. Through a MATLAB experiment, we show that MUcPF is significantly better in terms of economy and efficiency to establish a hybrid path between every pair of hosts in the network. In particular, it required 5%-15% less investment to achieve 100% path coverage compared to other algorithms. The results show the coverage consistency of MMHcPF on each individual path along with gains in terms of cost and efficiency. It takes 5%-20% less investment to achieve certain hop coverage target compared to other existing algorithms.
A vehicular-fog (VF) system as an emerging platform consists of electric vehicles with computing ... more A vehicular-fog (VF) system as an emerging platform consists of electric vehicles with computing resources that are mostly under-utilized. This paper considers a two-tier federated Edge and Vehicular-Fog (EVF) system, where edge systems may partially offload user traffic to nearby VFs for potential cost reduction. Offloading configuration is to determine the ratios and targets of offloading traffic for maximal cost reduction, which is formulated as a mixed integer programming problem in this paper. We first present a decentralized offloading configuration protocol (DOCP) for an individual edge system to set up its own offloading configuration. We then propose a matching protocol among multiple edge systems to resolve resource contention when they simultaneously request resources from the same VF. Simulation results show that the proposed approach can leverage the heterogeneity of cost and capacity between edge systems and VFs. The proposed protocol outperforms greedy approaches by at most 40% and is comparable to a centralized off-line approach that is based on Particle Swarm Optimization.
IEEE Transactions on Network and Service Management, Mar 1, 2018
Network function virtualization (NFV), with 1 its virtualization technologies, brings cloud compu... more Network function virtualization (NFV), with 1 its virtualization technologies, brings cloud computing to 2 networking. Virtualized network functions (VNFs) are chained 3 together to provide the required functionality at runtime on 4 demand. It has a direct impact on power consumption depending 5 on where and how these VNFs are placed and chained to accom-6 plish certain demands as the power consumption of a physical 7 machine (PM) depends on its traffic load. One of the advantages 8 of VNF placement over traditional virtual machine placement 9 is that virtualization is not limited solely to servers. The PMs, 10 including the servers and varying loads to these machines and 11 their utilization, are critical issues related to the network's energy 12 consumption. In this paper, we designed a dynamic energy-saving 13 model with NFV technology using an M/M/c queuing network 14 with the minimum capacity policy where a certain amount of load 15 is required to start the machine, which increases the utilization of 16 the machine and avoids frequent changes of the machines' states. 17 We formulate an energy-cost optimization problem with capacity 18 and delay as constraints. We propose a dynamic placement of 19 VNF chains (DPVC) heuristic solution to the NP-hard problem. 20 The results show that the DPVC solution performs better and 21 saves more energy. It uses 45%-55% less active nodes to satisfy 22 the requested demands and increases the utilization of the active 23 nodes by 40%-50% compared to other algorithms.
Over the past 50 years, conventional network routing design has undergone substantial growth, evo... more Over the past 50 years, conventional network routing design has undergone substantial growth, evolving from small networks with static nodes to large systems connecting billions of devices. This progress has been achieved through the separation of concerns principle, which entails integrating network functionalities into a graph or random network design and employing specific network protocols to facilitate diverse communication capabilities. This paper aims to highlight the potential of designing routing techniques for quantum networks, which exhibit unique properties due to quantum mechanics. Quantum routing design requires a substantial deviation from conventional network design protocols since it must account for the unique features of quantum entanglement and information. However, implementing these techniques poses significant challenges, such as decoherence and noise in quantum systems, restricted communication ranges, and highly specialized hardware prerequisites. The paper commences by examining essential research on quantum routing design methods and proceeds to cover fundamental aspects of quantum routing, associated quantum operations, and the steps necessary for building efficient and robust quantum networks. This paper summarizes the present state of quantum routing techniques, including their principles, protocols, and challenges, highlighting potential applications and future directions.
A vehicular-fog (VF) system as an emerging platform consists of electric vehicles with computing ... more A vehicular-fog (VF) system as an emerging platform consists of electric vehicles with computing resources that are mostly under-utilized. This paper considers a two-tier federated Edge and Vehicular-Fog (EVF) system, where edge systems may partially offload user traffic to nearby VFs for potential cost reduction. Offloading configuration is to determine the ratios and targets of offloading traffic for maximal cost reduction, which is formulated as a mixed integer programming problem in this paper. We first present a decentralized offloading configuration protocol (DOCP) for an individual edge system to set up its own offloading configuration. We then propose a matching protocol among multiple edge systems to resolve resource contention when they simultaneously request resources from the same VF. Simulation results show that the proposed approach can leverage the heterogeneity of cost and capacity between edge systems and VFs. The proposed protocol outperforms greedy approaches by at most 40% and is comparable to a centralized off-line approach that is based on Particle Swarm Optimization.
Vehicular-fog system consists of vehicles with computing resources that are mostly under-utilized... more Vehicular-fog system consists of vehicles with computing resources that are mostly under-utilized. Therefore, an edge system may offload some workloads for remote execution at nearby vehicular-fogs. Whether this is cost-effective depends on not only the costs and computation capacities of vehicles but also the amount of workloads and associated latency constraint. In this paper, we consider a two-tier federated Edge and Vehicular-Fog (EVF) architecture and aim to minimize overall cost while meeting latency constraint by setting up an appropriate offloading configuration. We model this to a singleobjective mixed integer programming problem. To solve this mixed integer problem in real time we propose an iterative greedy algorithm using the queuing model. The results show, our proposed architecture reduces the cost of vehicular-fogs by 40-45% and the total cost by 35-40% compared to the existing architecture and help the edge to provide services beyond its capacity with specified latency constraint.
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