Raza Ul-Mustafa

Data aggregation in wireless sensor networks - exact and approximate algorithms

A fundamental challenge in the design of wireless sensor networks (WSNs) is to maximize their lifetimes. Data aggregation has emerged as a basic approach in WSNs in order to reduce the number of transmissions of sensor nodes, and hence minimizing the overall power consumption in the network. We study optimal data aggregation in WSNs. Data aggregation is affected by several factors, such as the placement of aggregation points, the aggregation function, and the density of sensors in the network. The determination of an optimal selection of aggregation points is thus extremely important. We present exact and approximate algorithms to find the minimum number of aggregation points in order to maximize the network lifetime. Our algorithms use a fixed virtual wireless backbone that is built on top of the physical topology. We also study the tradeoffs between energy savings and the potential delay involved in the data aggregation process. Numerical results show that our approach provides substantial energy savings.

Data aggregation and routing in Wireless Sensor Networks: Optimal and heuristic algorithms

A fundamental challenge in the design of Wireless Sensor Networks (WSNs) is to maximize their lifetimes especially when they have a limited and non-replenishable energy supply. To extend the network lifetime, power management and energy-efficient communication techniques at all layers become necessary. In this paper, we present solutions for the data gathering and routing problem with in-network aggregation in WSNs. Our objective is to maximize the network lifetime by utilizing data aggregation and in-network processing techniques. We particularly focus on the joint problem of optimal data routing with data aggregation en route such that the above mentioned objective is achieved. We present Grid-based Routing and Aggregator Selection Scheme (GRASS), a scheme for WSNs that can achieve low energy dissipation and low latency without sacrificing quality. GRASS embodies optimal (exact) as well as heuristic approaches to find the minimum number of aggregation points while routing data to the Base-Station (BS) such that the network lifetime is maximized. Our results show that, when compared to other schemes, GRASS improves system lifetime with acceptable levels of latency in data aggregation and without sacrificing data quality.

Design and provisioning of WDM networks with multicast traffic grooming

In this paper we consider the optimal design and provisioning of WDM networks for the grooming of multicast subwavelength traffic. We develop a unified framework for the optimal provisioning of different practical scenarios of multicast traffic grooming. We also introduce heuristic solutions. Optimal solutions are designed by exploiting the specifies of the problems to formulate Mixed Integer Linear Programs (MILPs). Specifically, we solve the generic multicast problem in which, given a set of multicast sessions and all destination nodes of a multicast session requiring the same amount of traffic, all demands need to be accommodated. The objective is to minimize the network cost by minimizing the number of higher layer electronic equipment and, simultaneously, minimizing the total number of wavelengths used. We also solve two interesting and practical variants of the traditional multicast problem, namely, multicasting with partial destination set reachability and multicasting with traffic thinning. For both variants, we also provide optimal as well as heuristic solutions. Also, the paper presents a number of examples based on the exact and heuristic approaches

Multicast traffic grooming in WDM networks

This paper considers the problem of grooming multicast traffic in WDM networks, with arbitrary mesh topologies. The problem is different from grooming of unicast traffic, since traffic can be delivered to destinations through other destinations in the same set, or through branching points. The paper presents an optimal Integer Linear Programming (ILP) formulation in order to minimize the cost of the network in terms of the number of SONET Add/Drop Multiplexers (ADM). The formulation also minimizes the number of wavelength channels used in the network, and does not allow bifurcation of traffic. Since the ILP formulation is able to solve limited size problems, the paper also introduces a heuristic approach to solve the problem.

On the optimal clustering in mobile ad hoc networks

A mobile ad hoc network (MANET) can be represented by a set of logical clusters with clusterheads (CHs) acting like virtual base-stations, hence forming a wireless virtual backbone. The role of clusterhead is a temporary one, which changes dynamically as the topology or other factors affecting it change. Finding the minimal set of CHs is an NP-complete problem. We study the performance tradeoffs between two clustering approaches. The first one is a simple clustering strategy, called virtual grid architecture (VGA), which is based on a fixed rectilinear virtual topology, while the second one is an optimal clustering strategy. We consider homogeneous as well as heterogeneous networks. First, for homogeneous MANETs with a large number of users and under the VGA clustering approach, we derive expressions for the number of CHs, worst case path length, and average case path length. We also derive expressions for the communication overhead. Second, we develop an integer linear program (ILP) that finds the optimal number of connected CHs in small to medium sized heterogeneous MANETs. Analytical and simulation results show that our proposed clustering algorithm (VGA), although being simple, is close to optimal.

Many-to-one traffic grooming with aggregation in WDM networks

Most of the network applications bandwidth requirements are far less than the bandwidth offered by a full wavelength in WDM networks. Hence, traffic grooming is needed to make efficient use of the available resources. In this paper we address the grooming of many-to-one traffic demands in WDM networks on arbitrary topologies. Traffic streams from different sources, but part of the same session and thus terminating at the same destination, can be aggregated using arbitrary, but application dependent, aggregation ratios. We provide optimal as well as heuristic solutions to the problem. The objective is to minimize the cost of the network, by minimizing the total number of the higher layer components and the total number of the wavelengths used in the network. One of the main contributions of this work is to provide a mixed integer linear solution, to an otherwise non-linear problem, by exploiting the specifics of routing and aggregation sub-problems, while still maintaining the optimality of the solution. The formulation is generic and can handle varying amounts of traffic from each source to a common destination, as well as arbitrary aggregation fractions of the data coming from the different sources. This fraction is made to be a function of the number of the streams participating in the aggregation. For the heuristic solution we developed a Dynamic Programming style approach that builds the solution progressively, going through a number of stages, while choosing the best partial solutions among a number of possible partial solutions at each stage

Grooming of non-uniform traffic on unidirectional and bidirectional rings

Traffic grooming in WDM networks is obtained by intelligently allocating the traffic onto a given set of wavelengths. This paper presents heuristics for grooming of non-uniform general traffic demands onto a given set of wavelengths available on a unidirectional or bidirectional ring. The objective is to minimize the number of higher layer equipment, like SONET Add/Drop Multiplexers (ADMs), or MPLS routers. We map the unidirectional ring onto a linear topology and develop a generalized two-step approach to solve the grooming problem on the mapped topology. In the first step, we allocate the traffic while minimizing the possible number of strings (each string being a collection of non-overlapping traffic streams) in a manner that yields the optimal number of strings in the linear topology case. We also prove the optimality of this step in the number of the strings (wavelengths). In the second step we employ a grouping technique to efficiently combine g strings onto a wavelength while minimizing the total number of the ADMs. We also address the problem of grooming the non-uniform traffic on a bidirectional ring by mapping it onto unidirectional rings, and applying the two-step approach. Moreover, in the case of bidirectional rings we propose an approach to route the traffic that reduces the total number of the required wavelengths and ADMs. The time complexity of our technique is at least an order of n less than other proposed approaches, where n is the total number of nodes in the network. The efficacy of the proposed technique has been demonstrated through a large number of experiments.

Optimal and approximate approaches for selecting proxy agents in mobile IP based network backbones

In a mobile environment, each mobile host should have a home agent on its home network that maintains a registry of the current location of the mobile host. This registry is normally updated every time a mobile host moves from one subnet to another. We study the tradeoff between the cost of updating the registry and the cost of searching for a mobile host while it is away from home. Using a set of special agents, called proxy agents, which implement a two-tier update process, the cost of updates could be reduced; however, the search cost might increase. We study different approaches to identify a set of proxy agents that minimizes the cost of search. In this paper, we use mathematical programming to obtain optimal solutions to the problem. We consider two situations: the cost of search measured by the sum of all search message costs, and the cost of search measured by the maximum cost of such messages. For these two respective cases we formulate the minimization of the cost of search as Min-Sum and Min-Max problems. For large networks in which the optimization problem may be intractable, we study three different approximate approaches: (1) clustering, (2) genetic algorithms, and (3) simulated annealing. Results of a large set of experiments are presented.

On the grooming of multicast traffic in WDM networks

In This work we consider the optimal dimensioning of optical networks for multicast traffic grooming problems on WDM networks under two practical scenarios. In both cases, for each multicast session the destination set consists of two disjoint subsets. In the first scenario only one subset of each multicast session must be accommodated while the other subset can only be accommodated if this results in no additional cost. In the second case, both subsets of each multicast session must be accommodated. However, each subset has different bandwidth requirements. We develop optimal and heuristic solutions for both the cases.

An integrated state assignment and flip-flop selection technique for FSM synthesis☆

Abstract In the automatic synthesis of Finite State Machines (FSMs), the state assignment and the choice of flip-flops significantly affect the cost of the combinational logic. To meet the demands of the increasing complexity of integrated circuits, we present an integrated state assignment and sequential element selection approach to synthesize area-efficient FSMs. The FSM synthesis approach is modeled as an optimization problem and is solved by using the guided evolutionary simulated annealing (GESA) technique. The GESA is a new type of parallel and distributed processing approach for searching the optimal solutions. Since the optimization problem at hand is NP-hard, a distributed algorithm for the GESA technique is developed and implemented on Network of Workstations (NOW) to speedup the search process. Promising speedups are obtained by running the distributed GESA algorithm on a NOW. Efficacy of the proposed technique is demonstrated by carrying out a comparison with other state-of-the-art techniques such as the MUSTANG, NOVA and JEDI for MCNC benchmarks. The proposed integrated state assignment and sequential element selection approach allows all types of flip-flops and offers considerable improvement in PLA area as compared to the existing techniques that use only D type flip-flops as the sequential element.