An average case analysis of the minimum spanning tree heuristic for the range assignment problem

We present an average case analysis of the minimum spanning tree heuristic for the range assignment problem on a graph with power weighted edges. It is well-known that the worst-case approximation ratio of this heuristic is 2. Our analysis yields the following results: (1) In the one dimensional case ($d = 1$), where the weights of the edges are 1 with probability $p$ and 0 otherwise, the average-case approximation ratio is bounded from above by $2-p$. (2) When $d =1$ and the distance between neighboring vertices is drawn from a uniform $[0,1]$-distribution, the average approximation ratio is bounded from above by $2-2^{-\alpha}$ where $\alpha$ denotes the distance power radient. (3) In Euclidean 2-dimensional space, with distance power gradient $\alpha = 2$, the average performance ratio is bounded from above by $1 + \log 2$

An ACO Algorithm for Effective Cluster Head Selection

This paper presents an effective algorithm for selecting cluster heads in mobile ad hoc networks using ant colony optimization. A cluster in an ad hoc network consists of a cluster head and cluster members which are at one hop away from the cluster head. The cluster head allocates the resources to its cluster members. Clustering in MANET is done to reduce the communication overhead and thereby increase the network performance. A MANET can have many clusters in it. This paper presents an algorithm which is a combination of the four main clustering schemes- the ID based clustering, connectivity based, probability based and the weighted approach. An Ant colony optimization based approach is used to minimize the number of clusters in MANET. This can also be considered as a minimum dominating set problem in graph theory. The algorithm considers various parameters like the number of nodes, the transmission range etc. Experimental results show that the proposed algorithm is an effective methodology for finding out the minimum number of cluster heads.Comment: 7 pages, 5 figures, International Journal of Advances in Information Technology (JAIT); ISSN: 1798-2340; Academy Publishers, Finlan

On the Complexity of Reducing the Energy Drain in Multihop Ad Hoc Networks

Numerous studies on energy-efficient routing for Multihop Ad Hoc Networks (MANET) look at extending battery life by minimizing the cost at the transmitting node. In this paper, we study the complexity of energy efficient routing when the energy cost of receiving packets is also considered. We first prove that, surprisingly, even when all nodes transmit at the same power, finding a simple unicast path that guarantees enough remaining energy locally at each node in the network then becomes an NP-complete problem. Second, we define formally the problem of finding a virtual backbone that minimized the overall energy cost and prove that this leads to a new NP-complete problem, that we name Connected Exact Cover. Finally, we provide a fully distributed algorithm to reduce the energy drain due to the number of redundant receptions in MANET protocols by offering a modification of the Multi-Point Relay selection scheme and give some provably optimal approximation bounds

On Optimizing the Backoff Interval for Random Access Schemes

To improve the channel throughput and the fairness of random access channels, we propose a new backoff algorithm, namely, the sensing backoff algorithm (SBA). A novel feature of the SBA scheme is the sensing mechanism, in which every node modifies its backoff interval according to the results of the sensed channel activities. In particular, every active node sensing the successful transmission decreases its backoff interval by an additive factor of the transmission time of a packet. In order to find the optimum parameters for the SBA scheme, we have studied the optimum backoff intervals as a function of different number of active nodes (N) in a single transmission area with pure ALOHA-type channels.We have found that the optimum backoff interval should be 4N times the transmission time of a packet when the random access channel operates under a pure ALOHA scheme. Based on this result, we have numerically calculated the optimum values of the parameters for SBA, which are independent of N. The SBA scheme operates close to the optimum backoff interval. Furthermore, its operation does not depend on the knowledge of N. The optimum backoff interval and the SBA scheme are also studied by simulative means. It is shown that the SBA scheme out-performs other backoff schemes, such as binary exponential backoff (BEB) and multiplicative increase linear decrease (MILD). As a point of reference, the SBA scheme offers a channel capacity of 0.19 when N is 10, while the MILD scheme can only offer 0.125. The performance gain is about 50%

Connectivity, Coverage and Placement in Wireless Sensor Networks

Wireless communication between sensors allows the formation of flexible sensor networks, which can be deployed rapidly over wide or inaccessible areas. However, the need to gather data from all sensors in the network imposes constraints on the distances between sensors. This survey describes the state of the art in techniques for determining the minimum density and optimal locations of relay nodes and ordinary sensors to ensure connectivity, subject to various degrees of uncertainty in the locations of the nodes

A Multichannel Medium Access Control and its Performance Estimation for Multihop Wireless Sensor Networks

The thesis proposes a three-tier architecture wireless sensor network to monitor the environment of wide rural area. To enhance the network throughput, a multichannel MAC, 2HCR, is developed. The performance of 2HCR is examined for both single and bidirectional traffics. For the bidirectional traffic, a simple priority support scheme is proposed to give a priority for command traffic. Also, a procedure to estimate the throughput of multihop networks is developed to be used in network design

Joint Routing and STDMA-based Scheduling to Minimize Delays in Grid Wireless Sensor Networks

In this report, we study the issue of delay optimization and energy efficiency in grid wireless sensor networks (WSNs). We focus on STDMA (Spatial Reuse TDMA)) scheduling, where a predefined cycle is repeated, and where each node has fixed transmission opportunities during specific slots (defined by colors). We assume a STDMA algorithm that takes advantage of the regularity of grid topology to also provide a spatially periodic coloring ("tiling" of the same color pattern). In this setting, the key challenges are: 1) minimizing the average routing delay by ordering the slots in the cycle 2) being energy efficient. Our work follows two directions: first, the baseline performance is evaluated when nothing specific is done and the colors are randomly ordered in the STDMA cycle. Then, we propose a solution, ORCHID that deliberately constructs an efficient STDMA schedule. It proceeds in two steps. In the first step, ORCHID starts form a colored grid and builds a hierarchical routing based on these colors. In the second step, ORCHID builds a color ordering, by considering jointly both routing and scheduling so as to ensure that any node will reach a sink in a single STDMA cycle. We study the performance of these solutions by means of simulations and modeling. Results show the excellent performance of ORCHID in terms of delays and energy compared to a shortest path routing that uses the delay as a heuristic. We also present the adaptation of ORCHID to general networks under the SINR interference model