M. P. Sebastian

Fully distributed cluster based routing architecture for mobile ad hoc networks

The design and analysis of routing protocols is an important issue in dynamic networks such as packet radio and ad-hoc wireless networks. Ad hoc wireless network is a dynamic multi-hop network, which is established by a group of mobile nodes on a shared wireless channel. The shared medium and the multi-hop nature of the wireless ad hoc networks pose fundamental challenges to the design of an effective resource allocation algorithm to maximize the aggregated utility of flows, maintaining basic fairness among the multiple flows. While the previously proposed scheduling algorithms have been shown to perform well in providing fair sharing of bandwidths among the single-hop wireless flows, they have not considered the multi-hop flow with an end-to-end perspective. Hierarchical, cluster-based routing greatly reduces the routing table sizes (compared to host-based routing) and the amount of routing related signaling traffic, at the expense of reducing path efficiency and generating some management traffic. This paper proposes a fully distributed cluster based routing algorithm for mobile ad hoc networks. The feasible path to a destination is calculated using the QoS information available with each cluster members. Non-overlapping clusters are created using the dynamic cluster creation algorithm. Packets are routed according to the QoS information available with each gateway node. The mobility issues are also handled in this routing architecture. Because of the hierarchical nature of architecture, the performance is unaffected by the increase in the number of mobile nodes. The cluster maintenance algorithm dynamically manages the handover and hence the efficiency is not degraded by node mobility.

SCAM: Scenario-based Clustering Algorithm for Mobile ad hoc networks

This paper proposes a scenario based, adaptive and distributed clustering algorithm SCAM (Scenario-based Clustering Algorithm for Mobile ad hoc networks). A distributed algorithm based on (k, r) - Dominating Set is used for the selection of clusterheads and gateway nodes, here k is the minimum number of clusterheads per node in the network and r is the maximum number of hops between the node and the clusterhead. From among the k dominating nodes, the non-clusterhead node can select the most qualified dominating node as its clusterhead. The quality of the clusterhead is calculated based on various metrics, which include connectivity, stability and residual battery power. Long-term service as clusterhead depletes their energy, causing them to drop out of the network. Similarly, the clusterhead with relatively high mobility than its neighbours leads to frequent clusterhead election process. This perturbs the stability of the network and adversely affects the performance of the network. Load balancing among clusterheads and correct positioning of clusterhead in a cluster are also vital to increase the life span of the network. The proposed algorithm periodically calculates the quality of all dominating nodes and if it goes below the threshold level it resigns the job as clusterhead and sends this message to all other member nodes. Since these nodes have k dominating nodes within r - hop distance, it can choose the current best-qualified node as its clusterhead. SCAM uses techniques to maintain the cluster structure as stable as possible with less control messages.

Enhancing the K-means Clustering Algorithm by Using a O(n logn) Heuristic Method for Finding Better Initial Centroids

With the advent of modern techniques for scientific data collection, large quantities of data are getting accumulated at various databases. Systematic data analysis methods are necessary to extract useful information from rapidly growing data banks. Cluster analysis is one of the major data mining methods and the k-means clustering algorithm is widely used for many practical applications. But the original k-means algorithm is computationally expensive and the quality of the resulting clusters substantially relies on the choice of initial centroids. Several methods have been proposed in the literature for improving the performance of the k-means algorithm. This paper proposes an improvement on the classic k-means algorithm to produce more accurate clusters. The proposed algorithm comprises of a O(n logn) heuristic method, based on sorting and partitioning the input data, for finding the initial centroids in accordance with the data distribution. Experimental results show that the proposed algorithm produces better clusters in less computation time.

A novel content classification scheme for web caches

Web caches are useful in reducing the user perceived latencies and web traffic congestion. Multi-level classification of web objects in caching is relatively an unexplored area. This paper proposes a novel classification scheme for web cache objects which utilizes a multinomial logistic regression (MLR) technique. The MLR model is trained to classify web objects using the information extracted from web logs. We introduce a novel grading parameter worthiness as a key for the object classification. Simulations are carried out with the datasets generated from real world trace files using the classifier in Least Recently Used-Class Based (LRU-C) and Least Recently Used-Multilevel Classes (LRU-M) cache models. Test results confirm that the proposed model has good online learning and prediction capability and suggest that the proposed approach is applicable to adaptive caching.

Scenario-Based Diameter-Bounded Algorithm for Cluster Creation and Management in Mobile Ad hoc Networks

The construction of stable and adaptive clusters providing good performance and faster convergence rate with minimal overhead is a challenging task in Mobile Ad hoc Networks (MANETs). This paper proposes a clustering technique for MANETs, which is distributed, dominating set based, weighted and adaptive to changes in the topology called Distributed Scenario-based Clustering Algorithm for Mobile ad hoc networks (DSCAM). The election of clusterheads and gateway nodes is based on (k, r) − Dominating set, where k s the minimum number of clusterheads per node in the network and r is the maximum number of hops between a node and its clusterhead. After selecting clusterheads, affiliation of other nodes with the clusterhead is decided based on the quality of clusterhead, which is a function of connectivity, stability, residual battery power and transmission rate. Among the k dominating nodes, non clusterhead nodes select the most qualified node as its clusterhead. DSCAM creates stable clusters with less overhead and maximizes the life span of the network. The performance of this algorithm is evaluated through simulation and the results are encouraging.

Dynamic multipath routing for MANETs — A QoS adaptive approach

A MANET is a collection of wireless mobile stations with limited resources that can exchange information each other without any fixed infrastructure. It is a challenging task to design an efficient routing protocol for MANETs which supports diverse quality requirements like road or accident guidance, health care applications, dynamic database access, E-Commerce and multiuser games. Recent research shows that single path routing protocols fail to overcome the limitations of MANET routing such as frequent link failures and dynamicity. Frequent route breaks lead to repeated route discovery process and thereby increased control overhead and packet drop. Multipath routing protocols reduce the overheads in MANET routing by reducing the number of route discoveries and provide more throughput. Most of the recent approaches to select and maintain alternative routes in multipath routing lack a common metric for route selection which selects routes based on specific quality characteristics of routes. In this paper we propose a new dynamic multipath routing method which avoids stale routes by periodic maintenance, provides route switching prior to route breakage. This method always selects the best quality route based on the value of a tunable route metric which is calculated dynamically by considering the durability, consistency and quality of all individual paths and thereby gives quality routes suitable for diverse QoS requirements.

A novel harmony search-K means hybrid algorithm for clustering gene expression data

Recent progress in bioinformatics research has led to the accumulation of huge quantities of biological data at various data sources. The DNA microarray technology makes it possible to simultaneously analyze large number of genes across different samples. Clustering of microarray data can reveal the hidden gene expression patterns from large quantities of expression data that in turn offers tremendous possibilities in functional genomics, comparative genomics, disease diagnosis and drug development. The k- ¬means clustering algorithm is widely used for many practical applications. But the original k-¬means algorithm has several drawbacks. It is computationally expensive and generates locally optimal solutions based on the random choice of the initial centroids. Several methods have been proposed in the literature for improving the performance of the k-¬means algorithm. A meta-heuristic optimization algorithm named harmony search helps find out near-global optimal solutions by searching the entire solution space. Low clustering accuracy of the existing algorithms limits their use in many crucial applications of life sciences. In this paper we propose a novel Harmony Search-K means Hybrid (HSKH) algorithm for clustering the gene expression data. Experimental results show that the proposed algorithm produces clusters with better accuracy in comparison with the existing algorithms.

A Revised Secure Authentication Protocol for IEEE 802.16 (e)

The WiMAX IEEE 802.16 (e) is defined as the Worldwide Interoperability for Microwave Access by the WiMAX Forum, formed in April 2001 to promote conformance and interoperability of the IEEE 802.16 standard, and it is officially known as Wireless MAN. The absence of physical boundaries makes in general a wireless network more vulnerable than a wired network. The IEEE 802.16 provides a security sublayer in the MAC layer to address the privacy issues across the fixed BWA (Broadband Wireless Access). Several proposals have been published to address the flaws in IEEE802.16 security after the release of IEEE802.16-2001. However, even with the modified version IEEE802.16-2004, the security problems still persist and many additional flaws have emerged. This paper examines the threats against the authentication protocols of WiMAX and proposes a new authentication protocol which is more reliable and secure. The proposed protocol is rigid against the attacks like Denial of service (DOS), Man-in-the-middle and replay.

Clustering Biological Data Using Enhanced k-Means Algorithm

With the advent of modern scientific methods for data collection, huge volumes of biological data are now getting accumulated at various data banks. The enormity of such data and the complexity of biological networks greatly increase the challenges of understanding and interpreting the underlying data. Effective and efficient Data Mining techniques are essential to unearth useful information from them. A first step towards addressing this challenge is the use of clustering techniques, which helps to recognize natural groupings and interesting patterns in the data-set under consideration. The classical k-means clustering algorithm is widely used for many practical applications. But it is computationally expensive and the accuracy of the final clusters is not guaranteed always. This paper proposes a heuristic method for improving the accuracy and efficiency of the k-means clustering algorithm. The modified algorithm is then applied for clustering biological data, the results of which are promising.

Distributed Security Scheme for Mobile Ad Hoc Networks

Secured communication in mobile ad hoc network is a crucial issue due to dynamic nature of the network topology. Due to lack of centralized control, issuing certificates from a centralized certification agent is not possible in ad hoc network. The major problem in providing security services in such infrastructureless networks is how to manage the cryptographic keys that are needed. The unique characteristics of mobile ad hoc networks causes a number of nontrivial challenges to security design such as open network architecture, shared wireless medium, stringent resource constraints and highly dynamic topology. In MANET any node may compromise the packet routing functionality by disrupting the route discovery process. These challenges make a case for building multi-fence security solution that achieves both extensive protection and desirable network performance. We propose a novel cluster based security scheme to protect mobile ad hoc network link layer and network layer operations of delivering packet over the multihop wireless channel. The dynamic network topology can be managed efficiently by the proposed cluster based architecture. A well-behaving node becomes a cluster member after the initial trust verification process. The membership validity period of a node depends on how long it has stayed and behaved well. Non overlapping clusters are created using the dynamic cluster creation algorithm. The cluster construction is fully distributed so efficiency is not degraded by node mobility.