Random Deployment

topadhyay is a record of an original research work carried out by him under my supervision and guidance in partial fulfillment of the requirements for the award of the degree of Master of Technology in Computer Science & Engineering with specialization in Information Security from the department of Computer Science and Engineering, National Institute of Technology Rourkela. Neither this thesis nor any part of it has been submitted for any degree or academic award elsewhere.

Dynamic wireless sensor network (DWSN) is a group of mobile sensor nodes deployed in an intended area. Secure communication in DWSNs depends on the existence of an efficient key management scheme. Because of the movements of sensor nodes and unknown mobility pattern, dynamic key management is an important issue in such networks. In this paper, we propose a new key management scheme, which uses key pre‐distribution and post‐deployment key establishment mechanisms for DWSNs. The proposed approach ensures that the two communicating nodes share at least one common key. It also provides efficient ways for key generation and revocation as well as addition or deletion of mobile sensor nodes. Compared with the other key management schemes, which are designed for DWSNs, our simulation and analytical results demonstrate the efficiency of the proposed approach in terms of confidentiality, resilience, memory usage, energy consumption and overhead. Copyright © 2014 John Wiley & Sons, Ltd.

Wireless sensor networks have enticed much of the spotlight from researchers all around the world, owing to its extensive applicability in agricultural, industrial and military fields. Energy conservation node deployment stratagems play a notable role for active implementation of Wireless Sensor Networks. Clustering is the approach in wireless sensor networks which improves energy efficiency in the network. The clustering algorithm needs to have an optimum size and number of clusters, as clustering, if not implemented properly, cannot effectively increase the life of the network. In this paper, an algorithm has been proposed to address connectivity issues with the aim of ensuring the uniform energy consumption of nodes in every part of the network. The results obtained after simulation showed that the proposed algorithm has an edge over existing algorithms in terms of throughput and networks lifetime.

In this study, we focus on the analytical derivation of the expected distance between all sensor nodes and the base station (i.e., E[dtoBS]) in a randomly deployed WSN. Although similar derivations appear in the related literature, to the best of our knowledge, our derivation, which assumes a particular scenario, has not been formulated before. In this specific scenario, the sensing field is a square-shaped region and the base station is located at some arbitrary distance to one of the edges of the square. Having the knowledge of E[dtoBS] value is important because E[dtoBS] provides a network designer with the opportunity to make a decision on whether it is energy-efficient to perform clustering for WSN applications that aim to pursue the clustered architectures. Similarly, a network designer might make use of this expected value during the process of deciding on the modes of communications (i.e., multi-hop or direct communication) after comparing it with the maximum transmission ranges of devices. Last but not least, the use of our derivation is not limited to WSN domain. It can be also exploited in any domain when there is a need for a probabilistic approach to find the average distance between any given number of points which are all assumed to be randomly and uniformly located in any square-shaped region and at a specific point outside this region.

In this study, we focus on the analytical derivation of the expected distance between all sensor nodes and the base station (i.e., E[dtoBS]) in a randomly deployed WSN. Although similar derivations appear in the related literature, to the best of our knowledge, our derivation, which assumes a particular scenario, has not been formulated before. In this specific scenario, the sensing field is a square-shaped region and the base station is located at some arbitrary distance to one of the edges of the square. Having the knowledge of E[dtoBS] value is important because E[dtoBS] provides a network designer with the opportunity to make a decision on whether it is energy-efficient to perform clustering for WSN applications that aim to pursue the clustered architectures. Similarly, a network designer might make use of this expected value during the process of deciding on the modes of communications (i.e., multi-hop or direct communication) after comparing it with the maximum transmission ranges of devices. Last but not least, the use of our derivation is not limited to WSN domain. It can be also exploited in any domain when there is a need for a probabilistic approach to find the average distance between any given number of points which are all assumed to be randomly and uniformly located in any square-shaped region and at a specific point outside this region.

In this study, we focus on the analytical derivation of the expected distance between all sensor nodes and the base station (i.e., E[dtoBS]) in a randomly deployed WSN. Although similar derivations appear in the related literature, to the best of our knowledge, our derivation, which assumes a particular scenario, has not been formulated before. In this specific scenario, the sensing field is a square-shaped region and the base station is located at some arbitrary distance to one of the edges of the square. Having the knowledge of E[dtoBS] value is important because E[dtoBS] provides a network designer with the opportunity to make a decision on whether it is energy-efficient to perform clustering for WSN applications that aim to pursue the clustered architectures. Similarly, a network designer might make use of this expected value during the process of deciding on the modes of communications (i.e., multi-hop or direct communication) after comparing it with the maximum transmission ranges of devices. Last but not least, the use of our derivation is not limited to WSN domain. It can be also exploited in any domain when there is a need for a probabilistic approach to find the average distance between any given number of points which are all assumed to be randomly and uniformly located in any square-shaped region and at a specific point outside this region.

In this study, we focus on the analytical derivation of the expected distance between all sensor nodes and the base station (i.e., E[dtoBS]) in a randomly deployed WSN. Although similar derivations appear in the related literature, to the best of our knowledge, our derivation, which assumes a particular scenario, has not been formulated before. In this specific scenario, the sensing field is a square-shaped region and the base station is located at some arbitrary distance to one of the edges of the square. Having the knowledge of E[dtoBS] value is important because E[dtoBS] provides a network designer with the opportunity to make a decision on whether it is energy-efficient to perform clustering for WSN applications that aim to pursue the clustered architectures. Similarly, a network designer might make use of this expected value during the process of deciding on the modes of communications (i.e., multi-hop or direct communication) after comparing it with the maximum transmission ranges of devices. Last but not least, the use of our derivation is not limited to WSN domain. It can be also exploited in any domain when there is a need for a probabilistic approach to find the average distance between any given number of points which are all assumed to be randomly and uniformly located in any square-shaped region and at a specific point outside this region.

Research in the field of Wireless Sensor Networks (WSNs) has been plagued by difficulties in performing realistic simulations. For instance, most of the existing coverage optimization techniques presuppose that the region covered by a sensor node is a disc characterized by the radio transmission range. This assumption is rigorously false because of the propagation phenomena including fading and shadowing. This paper investigates the impact of these radio propagation phenomena on the coverage optimization strategy in a WSN. We rely on the log-normal shadowing model to represent the effect of the environmental features on the WSN performance. We propose a coverage model taking into account irregular radio propagation. We carry out a mathematical analysis to compute the average number of targets a sensor would detect under both perfect and irregular propagation conditions. We also conduct simulations to assess our random deployment model with respect to the existing strategies.

Recent years have witnessed the deployments of
wireless sensor networks for mission-critical applications such
as battlefield monitoring and security surveillance. These appli-
cations often impose stringent Quality of Surveillance (QoSv)
requirements including low false alarm rate and short detection
delay. In practice, collaborative data fusion techniques that can
deal with sensing uncertainty and enable sensor collaboration
have been widely employed in sensor systems to achieve stringent
QoSv requirements. However, most previous analytical studies
on the surveillance performance of wireless sensor networks are
based on simplistic models (such as the disc model) that cannot
capture the stochastic and collaborative nature of sensing. In this
paper, we systematically analyze the fundamental relationship
between QoSv, network density, sensing parameters, and target
properties. The results show that data fusion is effective in
achieving stringent QoSv requirements, especially in the senarios
with low signal-to-noise ratios (SNRs). In contrast, the disc model
is only suitable when the SNR is sufficiently high. Our results
help understand the limitations of disc model and provide insights
into improving QoSv of sensor networks using data fusion.

Recent years have witnessed the deployments of
wireless sensor networks for mission-critical applications such
as battlefield monitoring and security surveillance. These appli-
cations often impose stringent Quality of Surveillance (QoSv)
requirements including low false alarm rate and short detection
delay. In practice, collaborative data fusion techniques that can
deal with sensing uncertainty and enable sensor collaboration have
been widely employed in sensor systems to achieve stringent QoSv
requirements. However, most previous analytical studies on the
surveillance performance of wireless sensor networks are based
on simplistic models (such as the disc model) that cannot capture
the stochastic and collaborative nature of sensing. In this paper,
we systematically analyze the fundamental relationship between
QoSv, network density, sensing parameters, and target properties.
The results show that data fusion is effective in achieving stringent
QoSv requirements, especially in the senarios with low signal-to-
noise ratios (SNRs). In contrast, the disc model is only suitable
when the SNR is sufficiently high. Our results help understand
the limitations of disc model and provide insights into improving
QoSv of sensor networks using data fusion.

Wireless sensor networks have many applications, vary in size, and are deployed in a wide variety of areas. They are often deployed in potentially adverse or even hostile environment so that there are concerns on security issues in these networks. Sensor nodes used to form these networks are resource-constrained, which make security applications a challenging problem. Efficient key distribution and management mechanisms are needed besides lightweight ciphers. Many key establishment techniques have been designed to address the tradeoff between limited memory and security, but which scheme is the most effective is still debatable. In this paper, we provide a survey of key management schemes in wireless sensor networks. We notice that no key distribution technique is ideal to all the scenarios where sensor networks are used; therefore the techniques employed must depend upon the requirements of target applications and resources of each individual sensor network.

Widespread utilization of mobile ad hoc networks (MANETs), which communicate via broadcast wireless channels without any sort of infrastructure, raises security concerns. Introduction of identity-based cryptography (IBC) shed some light to security problems of MANETs. Key management (KM) plays significant role in network security. Although many proposals are suggested for identity based KM, they usually assume a trusted set of nodes during network initialization, which is not the case in many real world applications. In this paper, a novel identity based KM method is proposed which utilizes Pedersen’s verifiable secret sharing method. By distributing shared secret and key generation role among network nodes, proposed method provides high levels of availability and scalability, while eliminating single point of failure. The proposed method provides a mechanism to check the validity of secret shares, which are generated by network nodes. To illustrate the effectiveness and capabilities of proposed methods, they are simulated and compared with the performance of the existing methods.

WSNs are becoming an appealing research area due to their several application domains. The performance of WSNs depends on the topology of sensors and their ability to adapt to changes in the network. Sensor nodes are often resource constrained by their limited power, less communication distance capacity, and restricted sensing capability. Therefore, they need to cooperate with each other to accomplish a specific task. Thus, clustering enables sensor nodes to communicate through the cluster head node for continuous communication process.

The development of technologies such as Mobile and Adhoc networks have made the distributed environments widely accepted as they allows large scale support for resource sharing infrastructure. One of the challenging issues for such environments is secure authentication. We considered the role of threshold cryptography to provide advanced security for the MANETs, revealing the authorization process using threshold digital signature, proxy signature and multi-signature in ID-based and CA-based structures. In this paper after taking a review of various proposed schemes, problems and attacks for MANETs and their solutions, In order to make any system secure, the security services such as authentication, confidentiality, integrity, availability and non repudiation must be satisfied. However, in case of distributed environment, separate and advanced security techniques have to be implemented. As mentioned earlier, one the major challenge that needs to be addressed is security of authentication. We conclude some issues and determine some challenges that can take place in future.

Many papers have been proposed in order to increase the wireless sensor networks performance; This kind of network has limited resources, where the energy in each sensor came from a small battery that sometime is hard to be replaced or recharged. Transmission energy is the most concern part where the higher energy consumption takes place. Clustered hierarchy has been proposed in many papers; in most cases, it provides the network with better performance than other protocols. In our paper, first we discuss some of techniques, relates to this protocol, that have been proposed for energy efficiency; some of them were proposed to provide the network with more security level. Our proposal then suggests some modifications to some of these techniques to provide the network with more energy saving that should lead to high performance; also we
apply our technique on an existing one that proposed to increase the security level of cluster sensor networks.

Mobile ad hoc networks (MANETs) are popularly known to their mobility and ease of usage. These networks are a set of identical nodes that move freely to communicate among networks and they are represented as a set of clusters. However, their wireless and active natures cause them to be more susceptible to various types of security attacks and transmission energy consumption so that they drop out of the network easily. Now-a-days the major challenge of MANETS is to endow with the assurance to the secure network services and also to provide a nearby balance of load for the cluster-heads. To meet this confront, certificate revocation with load balancing is an important central component to provide security and energy conservation in the network communications. In this paper, we focus on load balancing clustering to widen the lifetime of the cluster-head for a maximum time before allowing it to withdraw so as to distribute the responsibility to other legitimate nodes in the cluster to act as a cluster-head along with the issue of certificate revocation process. For quick, accurate, secure certificate revocation and to conserve energy, we propose the CCRV with Load Balancing Clustering scheme where we can reduce the burden of the cluster along with secure certificate revocation. In particular, to minimize the transmission energy consumption, we use the master slave model to operate the network with longer lifetime and we propose load balancing mechanism to enhance the lifetime of the cluster-head.

In this paper, we address key management in cluster-based mobile ad hoc networks (MANETs). We present a fully-distributed IDbased multiple secrets key management scheme (IMKM). This scheme is implemented via a combination of ID-based multiple secrets and threshold cryptography. Ensuring secure communication in an ad hoc network is extremely challenging because of the dynamic nature of the network and the lack of centralized management. Our proposed analysis includes the effect of packet generation model, random deployment of sensors, dynamic cluster head assignment, data compression, and energy consumption model at the sensors. a new protocol called Equalized Cluster Head Election Routing Protocol (ECHERP), which pursues energy conservation through balanced clustering, is proposed. Performance evaluation of ECHERP is carried out through simulation tests. We also present a novel key predistribution scheme that uses deployment knowledge to divide deployment regions into overlapping clusters, each of which has its own distinct key space. Through careful construction of these clusters, network resilience is improved, we focus on the management of encryption keys in large-scale clustered WSNs. We propose a novel distributed key management scheme based on Exclusion Basis Systems (EBS); a combinatorial formulation of the group key management problem. Initially, clusters are formed in the network and the cluster heads are selected based on the energy cost, coverage and processing capacity. The sink assigns cluster key to every cluster and an EBS key set to every cluster head. The EBS key set contains the pairwise keys for intra-cluster and inter-cluster communication. During data transmission towards the sink, the data is made to pass through two phases of encryption thus ensuring security in the network. Our results include performance evaluation in terms of security metrics in clustered WSN and a detailed analysis of resource utilization.

Research in the field of Wireless Sensor Networks (WSNs) has been plagued by difficulties in performing realistic simulations. For instance, most of the existing coverage optimization techniques presuppose that the region covered by a sensor node is a disc characterized by the radio transmission range. This assumption is rigorously false because of the propagation phenomena including fading and shadowing. This paper investigates the impact of these radio propagation phenomena on the coverage optimization strategy in a WSN. We rely on the log-normal shadowing model to represent the effect of the environmental features on the WSN performance. We propose a coverage model taking into account irregular radio propagation. We carry out a mathematical analysis to compute the average number of targets a sensor would detect under both perfect and irregular propagation conditions. We also conduct simulations to assess our random deployment model with respect to the existing strategies.

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