Virtual dynamic backbone for mobile ad hoc networks

Lou

International Journal of Distributed Sensor Networks

et al. 2013

Target tracking is a typical and important application of wireless sensor networks (WSNs). In consideration of the network scalability and energy efficiency for target tracking in large-scale WSNs, it has been employed as an effective solution by organizing the WSNs into clusters. However, tracking a moving target in cluster-based WSNs suffers a boundary problem when the target moves across or along the boundaries of clusters, as the static cluster membership prevents sensors in different clusters from sharing information. In this paper, we propose a novel mobility management protocol, called hybrid cluster-based target tracking (HCTT), which integrates on-demand dynamic clustering into a cluster-based WSN for target tracking. By constructing on-demand dynamic clusters at boundary regions, nodes from different static clusters that detect the target can temporarily share information, and the tracking task can be handed over smoothly from one static cluster to another. As the target moves, static clusters and on-demand dynamic clusters alternately manage the target tracking task. Simulation results show that the proposed protocol performs better in tracking the moving target when compared with other typical target tracking protocols.

Section: International Journal Of Distributed Sensor Networkmentioning

confidence: 99%

“…For example, it facilitates spatial reuse of resources to increase the system capacity [2]; it also benefits local collaboration and routing [3,4]. Recently, the cluster structure is gradually adopted for solving the target tracking problem [5][6][7][8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Cluster-Based Target Tracking Protocol for Wireless Sensor Networks

Lou

International Journal of Distributed Sensor Networks

et al. 2013

“…Clustering schemes make it easier in responding to changes caused by network dynamics, node mobility, unpredicted failures and local changes. Since these changes need to be managed and detected within individual clusters only [11,12].…”

Section: Why Clustering In Wsns?mentioning

confidence: 99%

A Review Study on Analytical Estimation of Optimal Number of Clusters in Wireless Sensor Networks

Kumar

Dhok

Tripathi

et al. 2014

TNC

To improve energy efficiency, total network scalability and data aggregation in Wireless Sensor Networks (WSNs), sensor nodes are often grouped into disjoint and mostly non-overlapping subsets called clusters. To provide an energy-efficient system by clustering, there are three main challenges. First is to find the optimum number of nodes in a specific cluster, second is to find the optimum number of clusters in the network and the third is to find the optimum position of Cluster Head (CH) in a specific cluster. Selecting an optimum number of clusters in WSNs provide greater improvement in terms of system scalability, energy efficiency, collision reduction, network lifetime, latency, and efficient routing backbone in the network. Selection of optimal number of clusters in WSNs is affected by level at which WSNs is modeled viz. Radio Energy Model Level, Network Model Level and Clustering Level. The objective of this paper is to present a state-of-the-art survey of distinct analytical methods used to calculate the optimum number of clusters, and its time-line comparative analysis based on network type, mathematical formula for an optimal number of clusters, base station positioning, energy model, strengths, weaknesses and applications of WSNs. We have also discussed the impact of different parameters on selecting the optimal number of clusters in WSNs.

Proceedings of the 3rd ACM International Symposium on Mobile Ad Hoc Networking &Amp; Computing - MobiHoc '02

“…This provides a very useful tool for the user to view the current state of the test subject (ad-hoc network software). For example, some ad-hoc routing algorithms assign different roles to different nodes, such as selecting nodes to be "cluster heads" (e.g., ZRP [5]), or marking nodes "green" or "black" color depending on its internal state (e.g., VDBP [9]). If we are to test these algorithms, we can instrument the routing code so that it sends a command to the master controller whenever the node changes color, and the corresponding node on the canvas board will change color accordingly.…”

Section: Ad-hoc Network Visualizationmentioning

confidence: 99%

An integrated environment for testing mobile ad-hoc networks

Zhang¹,

Li²

2002

Mobile Ad-Hoc Network (MANET) has become an increasingly active research area with a plethora of work in ad-hoc routing, media access, and protocols, etc. However, much of the effort so far has been in simulation with only a few systems that have ever been implemented and none that we know have been tried in a scale beyond a dozen nodes. One reason is the high complexity involved in implementing and testing actual ad-hoc networks, and the lack of software tools for doing so. We have thus built an inexpensive and flexible environment to support such tasks and to facilitate network research. The core component is a mobility emulator to test an ad-hoc network of virtually any scale and with any mobility scenario without actually moving the nodes physically.