Nabanita Das

Channel assignment using genetic algorithm based on geometric symmetry

The paper deals with the channel assignment problem in a hexagonal cellular network with two-band buffering, where channel interference does not extend beyond two cells. Here, for cellular networks with homogeneous demands, we find some lower bounds on the minimum bandwidth required for various relative values of s/sub 0/, s/sub 1/, and s/sub 2/, the minimum frequency separations to avoid interference for calls in the same cell, or in cells at distances of one and two, respectively. We then present an algorithm for solving the channel assignment problem in its general form using the elitist model of genetic algorithm (EGA). We next apply this technique to the special case of hexagonal cellular networks with two-band buffering. For homogeneous demands, we apply EGA for assigning channels to a small subset of nodes and then extend it for the entire cellular network, which ensures faster convergence. Moreover, we show that our approach is also applicable to cases of nonhomogeneous demands. Application of our proposed methodology to well-known benchmark problems generates optimal results within a reasonable computing time.

Mobile user tracking using a hybrid neural network

In this paper, a novel technique for location prediction of mobile users has been proposed, and a paging technique based on this predicted location is developed. As a mobile user always travels with a destination in mind, the movements of users, are, in general, preplanned, and are highly dependent on the individual characteristics. Hence, neural networks with its learning and generalization ability may act as a suitable tool to predict the location of a terminal provided it is trained appropriately by the personal mobility profile of individual user. For prediction, the performance of a multi-layer perceptron (MLP) network has been studied first. Next, to recognize the inherent clusters in the input data, and to process it accordingly, a hybrid network composed of a self-organizing feature map (SOFM) network followed by a number of MLP networks has been employed. Simulation studies show that the latter performs better for location management. This approach is free from all unrealistic assumptions about the movement of the users. It is applicable to any arbitrary cell architecture. It attempts to reduce the total location management cost and paging delay, in general.

A distributed algorithm for load-balanced routing in multihop wireless sensor networks

For multi-hop wireless sensor networks, this paper presents a simple, loop-free, distributed algorithm to select path for data gathering from each sensor node to the sink node that attempts to balance the load in terms of power dissipation in communication at individual nodes with 100% data aggregation to enhance the lifetime of the network as a whole. It requires just a one-time computation during the initialization of the network, and the paths remain static unless the routing tree gets partitioned due to faults etc. The performance of the proposed scheme has been compared with some conventional centralized routing techniques, namely the minimum hop routing, the shortest power path routing and the minimum spanning tree routing by simulation. In all the cases, the proposed algorithm results improved lifetime.

O(n) routing in rearrangeable networks

Abstract In (2n−1)-stage rearrangeable networks, the routing time for any arbitrary permutation is Ω(n2) compared to its propagation delay O(n) only. Here, we attempt to identify the sets of permutations, which are routable in O(n) time in these networks. We define four classes of self-routable permutations for Benes network. An O(n) algorithm is presented here, that identifies if any permutation P belongs to one of the proposed self-routable classes, and if yes, it also generates the necessary control vectors for routing P. Therefore, the identification, as well as the switch setting, both problems are resolved in O(n) time by this algorithm. It covers all the permutations that are self-routable by anyone of the proposed techniques. Some interesting relationships are also explored among these four classes of permutations, by applying the concept of ‘group-transformations’ [N. Das, B.B. Bhattacharya, J. Dattagupta, Hierarchical classification of permutation classes in multistage interconnection networks, IEEE Trans. Comput. (1993) 665–677] on these permutations. The concepts developed here for Benes network, can easily be extended to a class of (2n−1)-stage networks, which are topologically equivalent to Benes network. As a result, the set of permutations routable in a (2n−1)-stage rearrangeable network, in a time comparable to its propagation delay has been extended to a large extent.

A cross-layer distributed TDMA scheduling for data gathering with minimum latency in wireless sensor networks

In a wireless sensor network, given a routing tree for data gathering from individual nodes to the sink node, this paper presents a simple, distributed algorithm for assigning time slot to each node for conflict-free communication, such that the maximum latency in data gathering at the sink is minimized. It requires just a one-time computation during the initialisation of the network provided the nodes remain static. Simulation studies have been done to evaluate the performance in terms of latency, and the average duty cycle.

Isomorphism of conflict graphs in multistage interconnection networks and its application to optimal routing

A study on the isomorphism of conflict graphs in multistage interconnection networks (MINs) and its applications is outlined. A concept called group-transformation is introduced for the baseline network, which induces an equivalence partition on the set of all permutations. All members belonging to the same equivalence class have isomorphic conflict graphs. Thus, determination of conflict resolution of one permutation results in determination of conflict resolution of all other equivalent members. The BPCL (bit-permute-closure) class of permutations is defined, for which the conflict resolution problem can be settled in linear time by an earlier algorithm developed only for the BPC (bit-permute-complement) permutations. It is proved that for an N*N MIN, mod BPCL mod >or=n 2N-1, in contrast to mod BPC mod n 2n, (nlog/sup 2/ N). Conflict graphs for BPCL permutations are also characterized. An O(N) time algorithm to check membership of a given permutation to the BPCL class is described. All of these results are generalized to extend their applicability to other unique-path full-access MINs. >

A New Approach to Efficient Channel Assignment for Hexagonal Cellular Networks

Given a hexagonal cellular network with specific demand Vector and frequency separation constraints, we introduce the concept of a critical block of the network, that leads us to an efficient chann...

Localized algorithm for connected set cover partitioning in wireless sensor networks

In this paper, given a random distribution of sensor nodes, we pose the problem of finding maximum number of connected set covers such that each set can guarantee the required coverage of the region of interest. It requires just a one-time computation during initialization. Once the connected set covers are known, the sets may remain active in a round robin fashion to cover the region enhancing the life time of the network significantly. Firstly, two centralized greedy algorithms have been proposed to solve the problem from two different view points. But since centralized algorithms are not suitable for large self-organized sensor networks, a localized algorithm has been proposed finally that uses only local information at individual nodes to find a solution. Simulation studies show that these algorithms can enhance the network lifetime manifold, and most interestingly the performance of the distributed algorithm is comparable with the centralized ones in terms of number of partitions though it requires much less computation and communication overhead.

Distributed Data Gathering Scheduling in Multihop Wireless Sensor Networks for Improved Lifetime

For a multihop sensor network with n sensors, this paper presents an O(n) distributed greedy algorithm for extracting a rooted spanning tree to improve the lifetime of the overall network. It spontaneously determines a data gathering schedule from the sensors towards the base station (the root). No global knowledge about the topology is required for the computation and also each sensor does not need to access the base station directly. Simulation studies show that in terms of system lifetime, the proposed algorithm significantly outperforms the scheduling based on the minimum spanning tree (MST), or the shortest path (SP) routing techniques. Performance comparison with PEGASIS shows that the proposed algorithm performs better as more and more nodes die out

Self-organized area coverage in wireless sensor networks by limited node mobility

For wireless sensor networks, monitoring large inaccessible areas where deterministic node deployment is not possible, self-organized techniques are in demand to cover an area using optimal number of nodes. In this paper, given an initial random deployment of mobile sensor nodes, we propose a simple and novel technique for self-organized node movement to satisfy the coverage of the given region of interest using a least number of nodes, such that the maximum node displacement is minimized. We present a simple centralized algorithm and also a distributed version of it for node placement. Moreover, in case of a node failure, a distributed fault recovery algorithm is proposed to replace it locally utilizing the available free nodes. Analysis, simulation, and comparison studies show that the proposed algorithms with less neighborhood information result in significant improvement in terms of average and maximum displacement of a node, rounds of communication, and number of active nodes.