Sasthi C. Ghosh

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.

A survey on the channel assignment problem in wireless networks

Efficient allocation of channels for wireless communication in different network scenarios has become an extremely important topic of recent research. The main challenge lies in the fact that the channel allocation problem is NP-complete. Because of a maximum allowable time limit imposed in practical situations for allocation of channels, sometimes we may need to be satisfied with a near-optimal solution. In this correspondence, we present a discussion on the various challenges and approaches that have been used by different researchers to solve the problem of channel allocation taking into account different interference issues and efficient utilization of available communication channels for cellular mobile (including multimedia communication) environment and cognitive radio based networks. Copyright

Stochastic VM Multiplexing for Datacenter Consolidation

Virtual machine (VM) placement for Datacenter (DC) consolidation is a challenging problem, particularly in the face of VM workload fluctuation. In this paper, we present a stochastic model for optimization of DC consolidation and propose intelligent strategies for statistical VM multiplexing on physical machines (PMs) to ensure optimal use of hardware resources, while providing a service guarantee. We have provided an optimal strategy by modeling and solving the problem as a stochastic integer programming problem followed by a more scalable strategy based on a greedy heuristic. Extensive simulation based experimental results show that the strategies are more efficient in resource utilization while providing bounded service guarantees, than the traditional way of VM placement without any consideration to workload fluctuation.

A New Approach to Fast Near-Optimal Channel Assignment in Cellular Mobile Networks

This paper presents a novel method for solving channel assignment problems (CAPs) in hexagonal cellular networks with nonhomogeneous demands in a 2-band buffering system (where channel interference does not extend beyond two cells). The CAP with nonhomogeneous demand is first partitioned into a sequence of smaller subproblems, each of which has a homogeneous demand from a subset of the nodes of the original network. Solution to such a subproblem constitutes an assignment phase, where multiple homogeneous demands are assigned to the nodes corresponding to the subproblem, satisfying all the frequency separation constraints. The whole assignment process for the original network consists of a succession of multiple homogeneous assignments for all the subproblems. Based on this concept, we present a polynomial time approximation algorithm for solving the CAP for cellular networks having nonhomogeneous demands. Our proposed assignment algorithm, when executed on well-known benchmark instances, comes up with an assignment which is always within about 6 percent more than the optimal bandwidth, but requires a very small execution time (less than 5 millisecond on a HPxw8400 workstation). The proposed algorithm is very much suitable for real-life situations, where fast channel assignment is of primary importance, tolerating, however, a marginal deviation (6 percent) from the optimal bandwidth.

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...

An efficient channel assignment technique for hexagonal cellular networks

We first introduce the notion of a critical block of hexagonal cellular network with 2-band buffering, where the channel interference does not extend beyond two cells. For a network with a given demand vector and frequency separation constraints, we present an algorithm for finding its critical block. A novel idea of partitioning the critical block into several smaller sub-networks with homogeneous demands has been introduced which provides an elegant way of assigning frequencies to the critical block. This idea of partitioning is then extended for the frequency assignment to the rest of the network. The proposed algorithm provides an optimal assignment for eight well-known benchmark instances including the most difficult two. It is shown to be superior to the existing frequency assignment algorithms, reported so far, in terms of both bandwidth and computation time.

Multi-path routing In Cognitive Radio Networks for multimedia communication using sample division multiplexing

We propose a novel scheme for multi-path routing in a Cognitive Radio Network (CRN) for multimedia communication, even when a contiguous band of required width is not available for any hop in the route. The proposed scheme is based on an extension of the idea of Sample Division Multiplexing (SDM) as given in [1] for single-hop communication. Starting from the source node, we first explore the available (free) number of channels (not necessarily contiguous) between every pair of 1-distance neighbor nodes by the help of appropriate control messages. With the information gathered from this step, the network graph G is constructed. We run the max-flow algorithm [8] on this network graph to find the set of routes between the source and the destination nodes so that the sum total of the usable numbers of channels through all these routes is equal to the required number of channels for the multimedia signal to be communicated. In essence, each data packet of the multimedia signal is split into several sub-packets following the basic concept given in [1] each of which needs much smaller bandwidth than the original packet, and these sub-packets are sent through all these routes to be eventually received by the destination node with the desired QoS. The time complexity of our proposed algorithm for this route discovery is O(pf + TSD), where p is the number of edges in the network graph (G), f is the maximum flow in G and TSD is the initialization time for constructing the network graph. We have shown that TSD is O(Δδmax), where Δ is the diameter and δmax is the maximum node degree of the network graph.

IMPROVED ALGORITHM FOR MINIMUM COST RANGE ASSIGNMENT PROBLEM FOR LINEAR RADIO NETWORKS

In the unbounded version of the range assignment problem for all-to-all communication in 1D, a set of n radio-stations are placed arbitrarily on a line; the objective is to assign ranges to these radio-stations such that each of them can communicate with the others (using at most n - 1 hops) and the total power consumption is minimum. A simple incremental algorithm for this problem is proposed which produces optimum solution in O(n3) time and O(n2) space. This is an improvement in the running time by a factor of n over the best known existing algorithm for the same problem.

An efficient heuristic algorithm for 2D h-hops range assignment problem

Given a set S of n radio-stations on a 2D plane and an integer h, the range assignment problem is to assign ranges to the members in S such that each member of S can communicate with all other members in S using at most h hops, and the sum of powers required for all the members in S is minimized. The general 2D h-hop range assignment problem is known to be NP-hard (A.E.F. Clementi et al, Proc. Symp. on Theor. Aspects of Comp. Sci. (STACS-00), pp. 651-660, 2000). We first consider some simplified variations of the problem and propose an efficient polynomial time algorithm for obtaining optimal solution. In the homogeneous version, where the range assigned to each radio-station is same (/spl rho/), we can obtain the minimum value of /spl rho/ in O(n/sup 3/logn) time in the worst case. In addition, if we consider the unbounded version of the homogeneous range assignment problem (i.e. h=n-1), then the optimal value of /spl rho/ can be obtained in O(n/sup 2/logn) time. Finally, we propose an efficient heuristic algorithm for the general h-hop range assignment problem in 2D, where the range of the radio stations may not be equal. Experimental results demonstrate that our heuristic algorithm runs fast and produces near-optimal solutions on randomly generated instances.

Optimising CDMA Cell Planning with Soft Handover

Soft handover (SHO) is one of the fundamental features of code division multiple access (CDMA) systems such as universal mobile telecommunication system (UMTS), and it is affected by the placement and density of cells. Inclusion of soft handover in optimization models for UMTS and CDMA cell site selection and configuration has previously been very limited but it is important for coverage because it can provide gain to the user. Some authors have excluded SHO on the basis of tractability while others have found that omitting SHO in planning gives adequate solutions. As such the incorporation of SHO remains an important component for definitive investigation in optimisation models for cell planning. In this paper we focus on the problem and effect of including SHO in cell planning optimisation. We introduce a new cell planning optimisation model that explicitly incorporates SHO and reduces computational complexity. Exact results can be obtained when the orthogonality factor is zero, while a conservative approximation of interference is used to generate lower bounds on coverage in the general case. We demonstrate the tractability of this model and show that it leads to improved lower bounds for coverage maximisation in network planning.