Matangini Chattopadhyay

Resource allocation in cloud using simulated annealing

One of the major problems in the domain of cloud computing is to allocate requests to resources maintaining high resource utilization. Many researchers have used heuristic algorithms, statistical methods, stochastic knapsack problem, and soft computing techniques to solve this problem. In this paper, we have utilized a variation of multi dimensional (multi parameter) bin packing to model the problem. We have also presented an efficient resource allocation algorithm using simulated annealing. Our approach can be generalized to solve resource allocation problem in multiple layers of cloud computing. Furthermore, we have carried out experiments to illustrate efficiency of our algorithm with respect to commonly used First Come First Serve (FCFS) resource allocation method.

Improved performance with novel utility functions in a game-theoretic model of medium access control in wireless networks

This paper presents a novel game-theoretic design to optimize the performance of medium access control (MAC) in wireless networks. The nodes of the network are modeled as selfish and rational players of a non-cooperative game. We define novel utility functions to capture their gain from channel access. We characterize the Nash equilibrium of the game and show that it is unique and non-trivial. This ensures a stable operating point from which no player has an incentive to deviate unilaterally and where every player has an equal non-trivial share of the transmission channel. Thus the selfish behavior of the nodes is used to ensure desirable properties of the network as a whole. The nodes follow a distributed update mechanism to reach the equilibrium. They need no message passing or network-wide information. We implement its asynchronous version in NS-2 and study the dynamics of the game. We compare, via simulations, our game model with the distributed coordination function (DCF) in IEEE 802.11 and a comparable game model in the literature. We observe that our design outperforms both these designs and provides much higher throughput and lower collision overhead over a very wide range of network sizes.

Game-Theoretic Modeling and Optimization of Contention-Prone Medium Access Phase in IEEE 802.16/WiMAX Networks

IEEE 802.16/WiMAX is an emerging standard for broadband wireless networks. It operates in both point-to-multipoint (PMP) and mesh modes. In the former, a number of subscriber stations communicate directly with a central base station. Although it supports different traffic classes characterized by distinct QoS requirements, the simplest is the best effort traffic. In this class, the subscriber stations first send bandwidth requests to the base station in a contention prone manner. Once the desired bandwidth is granted, scheduled transmissions take place. With increasing number of subscriber stations, due to media contention, collisions increase causing high loss to request packets and hence fall in data throughput. In this paper we address the issue by designing a new medium access control protocol GTMA for this random access phase, using ideas from non-cooperative game theory. We show that the resulting game converges to a unique non-trivial Nash equilibrium. NS-2 simulations confirm the reduction in packet collisions and consequent increase in system-wide data throughput and improvement in short-term fairness. To the best of our knowledge, this is one of the first applications of game-theoretic ideas in the explicit setting of contention control in IEEE 802.16/WiMAX networks.

Using self organizing map in wireless sensor network for designing energy efficient topologies

There are many challenges involving WSN design such as the energy resources optimization, the robustness and the network coverage. We address here the problem of energy-efficient topology design. A well designed dynamic topology and efficient routing algorithms may allow a large reduction on the energy consumption. As such type of network, the sensors are connected in an ad-hoc manner, without any deterministic way. This paper is concerned with applying standard routing protocols into wireless sensor network by using topology modified by Neural Network which proves to be energy efficient as compared with unmodified topology. Neural Network has been proved to be a powerful tool in the distributed environment. Here, to capture the true distributed nature of the Wireless Sensor Network (WSN), neural networks Self organizing Feature Map (SOFM) is used.

Wormhole Detection Based on Ordinal MDS Using RTT in Wireless Sensor Network

In wireless communication, wormhole attack is a crucial threat that deteriorates the normal functionality of the network. Invasion of wormholes destroys the network topology completely. However, most of the existing solutions require special hardware or synchronized clock or long processing time to defend against long path wormhole attacks. In this work, we propose a wormhole detection method using range-based topology comparison that exploits the local neighbourhood subgraph. The Round Trip Time RTT for each node pair is gathered to generate neighbour information. Then, the network is reconstructed by ordinal Multidimensional Scaling MDS followed by a suspicion phase that enlists the suspected wormholes based on the spatial reconstruction. Iterative computation of MDS helps to visualize the topology changes and can localize the potential wormholes. Finally, a verification phase is used to remove falsely accused nodes and identify real adversaries. The novelty of our algorithm is that it can detect both short path and long path wormhole links. Extensive simulations are executed to demonstrate the efficacy of our approach compared to existing ones.

Analysing topology control protocols in wireless sensor network using network evolution model

In the study of wireless ad hoc and sensor networks, clustering is an important research problem as it aims at maximizing network lifetime and minimizing latency. A large number of algorithms have been devised to compute “good” clusters in a WSN but few papers have tried to characterize these algorithms in an analytical manner. In this paper, we use a local world model to understand and characterize the functioning of three tree based clustering algorithms. In particular, we have chosen simple tree, CDS Rule K, and A3 topology construction protocols. Using our theoretical framework based on a complex network model, we have also tried to quantify some of the observed features of these algorithms such as number of cluster heads and average degree of the resultant graph. The theoretically obtained measures have reasonably matched with measures obtained by simulation studies.

Recovering a game model from an optimal channel access scheme for WLANs

Idle Sense is an optimal channel access scheme to achieve high throughput with high short-term fairness in IEEE 802.11 style wireless LANs. This paper recovers a non-cooperative game model from the protocol. We show that the control algorithm used by Idle Sense can be reverse-engineered so that each node implicitly maximizes a selfish local utility function. We prove the game has a Nash equilibrium which, under certain conditions, is unique with all nodes sharing the wireless channel equally. We perform extensive numerical simulations to get the equilibrium point for various network sizes and compare the performance of the model with IEEE 802.11 DCF. The achieved throughput at equilibrium is close to optimal.

A DiffServ Architecture for QoS-Aware Routing for Delay-Sensitive and Best-Effort Services in IEEE 802.16 Mesh Networks

In todays networks, the widespread use of real-time traffic such as video and audio applications demand special service guarantee in terms of throughput, delay, and jitter, thus making quality of service (QoS) a key problem. IEEE 802.16 mesh networks are likely to be the basis of next-generation last mile network connectivity. So, providing QoS is one of the major designing goals in IEEE 802.16 mesh network. While the standard defines five service classes for PMP mode, no standard defined service classes exist for mesh mode. In this paper, we describe a differentiated service (DiffServ) architecture for QoS support in IEEE 802.16 mesh network by considering a basic requirement for QoS guarantee—delay. A new cross-layer routing metric is proposed, namely, expected scheduler delay (ESD). An efficient distributed scheme is proposed to calculate ESD and route the packets using source routing mechanism. This scheme is capable of differentiating between delay sensitive and best-effort traffic and route packets accordingly. Finally, the results of the proposed scheme are compared with the standard schemes that take hop count as a routing metric.

Tuning holdoff exponents for performance optimization in IEEE 802.16 Mesh Distributed Coordinated Scheduler

The IEEE 802.16/WiMAX mesh standard is a promising technology to support next generation wireless broadband metropolitan area networks. The medium access control (MAC) layer of IEEE 802.16 mesh supports both centralized and distributed scheduling mechanisms. The coordinated distributed scheduling mechanism uses a pseudo-random election algorithm to determine the transmission times of the nodes. The holdoff exponent is an important parameter of scheduling and determines the channel contention time of a node. In this paper, we propose a novel distributed search protocol that each node uses to select the holdoff exponent that minimizes the expected delay between its two successive transmissions in the control channel. We analyze the scheduler performance in NS-2 for various kinds of traffic including TCP, UDP and VoIP. Simulation results show that our scheme performs better than the standard algorithm and other comparable schemes in terms of throughput and delay.

A novel distance-based iterative sequential KNN algorithm for estimation of missing values in microarray gene expression data

The presence of missing entries in DNA microarray gene expression datasets creates severe problems in downstream analysis because they require complete datasets. Though several missing value prediction methods have been proposed to solve this problem, they have limitations which may affect the performance of various analysis algorithms. In this regard, a novel distance based iterative sequential K-nearest neighbour imputation method ISKNNimpute has been proposed. The proposed distance is a hybridisation of modified Euclidean distance and Pearson correlation coefficient. The proposed method is a modification of KNN estimation in which the concept of reuse of estimation is considered using both iterative and sequential approach. The performance of the proposed ISKNNimpute method is tested on various time-series and non time-series microarray datasets comparing with several widely used existing imputation techniques. The experimental results confirm that the ISKNNimpute method consistently generates better results compared to other existing methods.