Distributed Maintenance of Anytime Available Spanning Trees in Dynamic Networks

We address the problem of building and maintaining distributed spanning trees in highly dynamic networks, in which topological events can occur at any time and any rate, and no stable periods can be assumed. In these harsh environments, we strive to preserve some properties such as cycle-freeness or the existence of a root in each tree, in order to make it possible to keep using the trees uninterruptedly (to a possible extent). Our algorithm operates at a coarse-grain level, using atomic pairwise interactions in a way akin to recent population protocol models. The algorithm relies on a perpetual alternation of \emph{topology-induced splittings} and \emph{computation-induced mergings} of a forest of spanning trees. Each tree in the forest hosts exactly one token (also called root) that performs a random walk {\em inside} the tree, switching parent-child relationships as it crosses edges. When two tokens are located on both sides of a same edge, their trees are merged upon this edge and one token disappears. Whenever an edge that belongs to a tree disappears, its child endpoint regenerates a new token instantly. The main features of this approach is that both \emph{merging} and \emph{splitting} are purely localized phenomenons. In this paper, we present and motivate the algorithm, and we prove its correctness in arbitrary dynamic networks. Then we discuss several implementation choices around this general principle. Preliminary results regarding its analysis are also discussed, in particular an analytical expression of the expected merging time for two given trees in a static context.Comment: Distributed Maintenance of Anytime Available Spanning Trees in Dynamic Networks, Poland (2013

A Recursive, Distributed Minimum Spanning Tree Algorithm for Mobile Ad Hoc Networks

We introduce a recursive (“anytime”) distributed algorithm that iteratively restructures any initial spanning tree of a weighted graph towards a minimum spanning tree while guaranteeing at each successive step a spanning tree shared by all nodes that is of lower weight than the previous. Each recursive step is computed by a different active node at a computational cost at most quadratic in the total number of nodes and at a communications cost incurred by subsequent broadcast of the new edge set over the new spanning tree. We show that a polynomial cubic in the number of nodes bounds the worst case number of such steps required to reach a minimum spanning tree and, hence, the number of broadcasts along the way. We conjecture that the distributed, anytime nature of this algorithm is particularly suited to tracking minimum spanning trees in (sufficiently slowly changing) mobile ad hoc networks

Performance evaluation of OnehopMANET

When used together, Peer-to-Peer overlays and MANET complement each other well. While MANET provides wireless connectivity without depending on any pre-existing infrastructure, P2P overlays provide data storage/retrieval functionality. However, both systems face common challenges: maintaining connectivity in dynamic and decentralized networks. In this paper we evaluate the performance of OnehopMANET[1] as a structured P2P over MANET system that uses cross-layering with a proactive underlay. We compare the performance of OnehopMANET with two recent structured P2P over MANET systems (MA-SP2P and E-SP2P) that use the same underlay protocol (OLSR) and that have been shown to outperform other proposals. Through simulation we show that OnehopMANET achieves a better performance in terms of file discovery delay, lookup fail rate and total traffic load for all the simulated scenarios

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

Identified the Cluster Based Stretch and Shrink Method Based On Load Balancing Algorithm for Ad Hoc Network Topology Stability

No Abstrac

QoS multicast routing protocol oriented to cognitive network using competitive coevolutionary algorithm

The human intervention in the network management and maintenance should be reduced to alleviate the ever-increasing spatial and temporal complexity. By mimicking the cognitive behaviors of human being, the cognitive network improves the scalability, self-adaptation, self-organization, and self-protection in the network. To implement the cognitive network, the cognitive behaviors for the network nodes need to be carefully designed. Quality of service (QoS) multicast is an important network problem. Therefore, it is appealing to develop an effective QoS multicast routing protocol oriented to cognitive network. In this paper, we design the cognitive behaviors summarized in the cognitive science for the network nodes. Based on the cognitive behaviors, we propose a QoS multicast routing protocol oriented to cognitive network, named as CogMRT. It is a distributed protocol where each node only maintains local information. The routing search is in a hop by hop way. Inspired by the small-world phenomenon, the cognitive behaviors help to accumulate the experiential route information. Since the QoS multicast routing is a typical combinatorial optimization problem and it is proved to be NP-Complete, we have applied the competitive coevolutionary algorithm (CCA) for the multicast tree construction. The CCA adopts novel encoding method and genetic operations which leverage the characteristics of the problem. We implement and evaluate CogMRT and other two promising alternative protocols in NS2 platform. The results show that CogMRT has remarkable advantages over the counterpart traditional protocols by exploiting the cognitive favors