FLOC-SPANNER: An O(1) time, locally self-stabilizing algorithm for geometric spanner construction in a wireless sensor network

Geometric spanners are a popular form of topology control in wireless networks because they yield an efficient, reduced interference subgraph for both unicast and broadcast routing.;In this thesis work a distributed algorithm for creation of geometric spanners in a wireless sensor network is presented. Given any connected network, we show that the algorithm terminates in O(1) time, irrespective of network size. Our algorithm uses an underlying clustering algorithm as a foundation for creating spanners, and only relies on the periodic heartbeat messages associated with cluster maintenance for the creation of the spanners. The algorithm is also shown to stabilize locally in the presence of node additions and deletions. The performance of our algorithm is verified using large scale simulations. The average path length ratio for routing along the spanner for large networks is shown to be less than 2.;Geometric Spanners is a well-researched topic. The algorithm presented in this thesis differs from other spanner algorithms in the following ways: 1. It is a distributed locally self-stabilizing algorithm. 2. It does not require location information for its operation. 3. Creates spanner network in constant time irrespective of network size and network density

Self-stabilization in self-organized multihop wireless networks

International audienceIn large scale multihop wireless networks, flat architectures are not scalable. In order to overcome this major drawback, clusterization is introduced to support self-organization and to enable hierarchical routing. When dealing with multihop wireless networks the robustness is a main issue due to the dynamicity of such networks. Several algorithms have been designed for the clusterization process. As far as we know, very few studies check the robustness feature of their clusterization protocols. Moreover, when it is the case, the evaluation is driven by simulations and never by a theoretical approach. In this paper, we show that a clusterization algorithm, that seems to present good properties of robustness, is self-stabilizing. We propose several enhancements to reduce the stabilization time and to improve stability. The use of a Directed Acyclic Graph ensures that the self-stabilizing properties always hold regardless of the underlying topology. These extra criterion are tested by simulations

Enhanced AODV Routing Protocol Using Leader Election Algorithm

Failure of communication link in mobile ADHOC network is major issue. For the failure of link the performance of network is degraded. Due to mobility of mobile node brake the communication link and path of routing is failed. For the repairing of routing node used various algorithm such as leader election, distributed and selection algorithm. The failure of link decease the performance of routing protocol in mobile ad-hoc network, for the improvement of quality of service in mobile ad-hoc network various authors proposed a different model and method for prediction of link. The prediction of link decreases the failure rate of mobile node during communication. The leader election algorithm plays a major role in link failure prediction algorithm the process of link failure prediction implied in form of distributed node distribution. Proposed a new link stability prediction method based on current link-related or user-related information in shadowed environments. The modified protocol acquired the process of thresholds priority Oder on the basic of neighbor’s node. The selection of neighbor node deepens on the mode operation in three sections. According to order of state create cluster of priority of group. After creation of group calculate average threshold value and compare each group value with minimum threshold value and pass the control message for communication. Through this process mode of activation state of node is minimized the time of route establishment and maintenance. The selection of proper node in minimum time and other node in sleep mode the consumption of power is reduces. We modified SBRP protocol for selection of node during on demand request node according to sleep and activation mode of communication. Each node locally assigned priority value of node. For the evaluation of performance used network simulator NS-2.35. And simulate two protocol one is AODV-LE protocol, these protocol patch are available for the simulation purpose. And another protocol is AODV-LE-ME. AODV-LE-ME protocol is modified protocol of leader election protocol for the selection of mobile node during the communication. DOI: 10.17762/ijritcc2321-8169.15016

Self-stabilizing k-clustering in mobile ad hoc networks

In this thesis, two silent self-stabilizing asynchronous distributed algorithms are given for constructing a k-clustering of a connected network of processes. These are the first self-stabilizing solutions to this problem. One algorithm, FLOOD, takes O( k) time and uses O(k log n) space per process, while the second algorithm, BFS-MIS-CLSTR, takes O(n) time and uses O(log n) space; where n is the size of the network. Processes have unique IDs, and there is no designated leader. BFS-MIS-CLSTR solves three problems; it elects a leader and constructs a BFS tree for the network, constructs a minimal independent set, and finally a k-clustering. Finding a minimal k-clustering is known to be NP -hard. If the network is a unit disk graph in a plane, BFS-MIS-CLSTR is within a factor of O(7.2552k) of choosing the minimal number of clusters; A lower bound is given, showing that any comparison-based algorithm for the k-clustering problem that takes o( diam) rounds has very bad worst case performance; Keywords: BFS tree construction, K-clustering, leader election, MIS construction, self-stabilization, unit disk graph

Self-stabilizing cluster routing in Manet using link-cluster architecture

We design a self-stabilizing cluster routing algorithm based on the link-cluster architecture of wireless ad hoc networks. The network is divided into clusters. Each cluster has a single special node, called a clusterhead that contains the routing information about inter and intra-cluster communication. A cluster is comprised of all nodes that choose the corresponding clusterhead as their leader. The algorithm consists of two main tasks. First, the set of special nodes (clusterheads) is elected such that it models the link-cluster architecture: any node belongs to a single cluster, it is within two hops of the clusterhead, it knows the direct neighbor on the shortest path towards the clusterhead, and there exist no two adjacent clusterheads. Second, the routing tables are maintained by the clusterheads to store information about nodes both within and outside the cluster. There are two advantages of maintaining routing tables only in the clusterheads. First, as no two neighboring nodes are clusterheads (as per the link-cluster architecture), there is no need to check the consistency of the routing tables. Second, since all other nodes have significantly less work (they only forward messages), they use much less power than the clusterheads. Therefore, if a clusterhead runs out of power, a neighboring node (that is not a clusterhead) can accept the role of a clusterhead. (Abstract shortened by UMI.)

Vers une structuration auto-stabilisante des réseaux Ad Hoc

International audienceIn this paper, we present a self-stabilizing asynchronous distributed clustering algorithm that builds non-overlapping k-hops clusters. Our approach does not require any initialization. It is based only on information from neighboring nodes with periodic messages exchange. Starting from an arbitrary configuration, the network converges to a stable state after a finite number of steps. Firstly, we prove that the stabilization is reached after at most n+2 transitions and requires (u+1)* log(2n+k+3) bits per node, whereΔu represents node's degree, n is the number of network nodes and k represents the maximum hops number. Secondly, using OMNet++ simulator, we performed an evaluation of our proposed algorithm.Dans cet article, nous proposons un algorithme de structuration auto-stabilisant, distribuéet asynchrone qui construit des clusters de diamètre au plus 2k. Notre approche ne nécessite aucuneinitialisation. Elle se fonde uniquement sur l’information provenant des noeuds voisins à l’aided’échanges de messages. Partant d’une configuration quelconque, le réseau converge vers un étatstable après un nombre fini d’étapes. Nous montrons par preuve formelle que pour un réseau de nnoeuds, la stabilisation est atteinte en au plus n + 2 transitions. De plus, l’algorithme nécessite uneoccupation mémoire de (u + 1) log(2n + k + 3) bits pour chaque noeud u où u représente ledegré (nombre de voisins) de u et k la distance maximale dans les clusters. Afin de consolider lesrésultats théoriques obtenus, nous avons effectué une campagne de simulation sous OMNeT++ pourévaluer la performance de notre solution

Self-stabilizing algorithms for Connected Vertex Cover and Clique decomposition problems

In many wireless networks, there is no fixed physical backbone nor centralized network management. The nodes of such a network have to self-organize in order to maintain a virtual backbone used to route messages. Moreover, any node of the network can be a priori at the origin of a malicious attack. Thus, in one hand the backbone must be fault-tolerant and in other hand it can be useful to monitor all network communications to identify an attack as soon as possible. We are interested in the minimum \emph{Connected Vertex Cover} problem, a generalization of the classical minimum Vertex Cover problem, which allows to obtain a connected backbone. Recently, Delbot et al.~\cite{DelbotLP13} proposed a new centralized algorithm with a constant approximation ratio of $2$ for this problem. In this paper, we propose a distributed and self-stabilizing version of their algorithm with the same approximation guarantee. To the best knowledge of the authors, it is the first distributed and fault-tolerant algorithm for this problem. The approach followed to solve the considered problem is based on the construction of a connected minimal clique partition. Therefore, we also design the first distributed self-stabilizing algorithm for this problem, which is of independent interest

A Self-Stabilizing K-Clustering Algorithm Using an Arbitrary Metric (Revised Version of RR2008-31)

32 pagesMobile ad hoc networks as well as grid platforms are distributed, changing, and error prone environments. Communication costs within such infrastructure can be improved, or at least bounded, by using k-clustering. A k-clustering of a graph, is a partition of the nodes into disjoint sets, called clusters, in which every node is distance at most k from a designated node in its cluster, called the clusterhead. A self-stabilizing asynchronous distributed algorithm is given for constructing a k-clustering of a connected network of processes with unique IDs and weighted edges. The algorithm is comparison-based, takes O(nk) time, and uses O(log n + log k) space per process, where n is the size of the network. This is the first distributed solution to the k-clustering problem on weighted graphs

FRCA: A Fuzzy Relevance-Based Cluster Head Selection Algorithm for Wireless Mobile Ad-Hoc Sensor Networks

Clustering is an important mechanism that efficiently provides information for mobile nodes and improves the processing capacity of routing, bandwidth allocation, and resource management and sharing. Clustering algorithms can be based on such criteria as the battery power of nodes, mobility, network size, distance, speed and direction. Above all, in order to achieve good clustering performance, overhead should be minimized, allowing mobile nodes to join and leave without perturbing the membership of the cluster while preserving current cluster structure as much as possible. This paper proposes a Fuzzy Relevance-based Cluster head selection Algorithm (FRCA) to solve problems found in existing wireless mobile ad hoc sensor networks, such as the node distribution found in dynamic properties due to mobility and flat structures and disturbance of the cluster formation. The proposed mechanism uses fuzzy relevance to select the cluster head for clustering in wireless mobile ad hoc sensor networks. In the simulation implemented on the NS-2 simulator, the proposed FRCA is compared with algorithms such as the Cluster-based Routing Protocol (CBRP), the Weighted-based Adaptive Clustering Algorithm (WACA), and the Scenario-based Clustering Algorithm for Mobile ad hoc networks (SCAM). The simulation results showed that the proposed FRCA achieves better performance than that of the other existing mechanisms