Sushma Jain

Impact of black hole and gray hole attack in AODV protocol

Security is one of the major issues in MANET due to dynamically changing topologies, lack of centralized monitoring, open medium and bandwidth constraint. Black hole and gray hole attacks are DOS attacks that pose a great threat to the network integrity. This paper exhibits the effects of these attacks on applying AODV protocol based on various performance metrics such as throughput, packet drop ratio, normalized routing load and number of dropped packets on parameters such as varying speed, number of nodes and pause time. Also a measure suggested to minimize black hole attack has also been analysed on the above metrics.

Data Aggregation in Wireless Sensor Networks: Previous Research, Current Status and Future Directions

Wireless sensor networks (WSNs) consist of large number of small sized sensor nodes, whose main task is to sense the desired phenomena in a particular region of interest. These networks have large number of applications such as habitat monitoring, disaster management, security and military etc. Sensor nodes are very small in size and have limited processing capability as these nodes have very low battery power. WSNs are also prone to failure, due to low battery power constraint. Data aggregation is an energy efficient technique in WSNs. Due to high node density in sensor networks same data is sensed by many nodes, which results in redundancy. This redundancy can be eliminated by using data aggregation approach while routing packets from source nodes to base station. Researchers still face trouble to select an efficient and appropriate data aggregation technique from the existing literature of WSNs. This research work depicts a broad methodical literature analysis of data aggregation in the area of WSNs in specific. In this survey, standard methodical literature analysis technique is used based on a complete collection of 123 research papers out of large collection of 932 research papers published in 20 foremost workshops, symposiums, conferences and 17 prominent journals. The current status of data aggregation in WSNs is distributed into various categories. Methodical analysis of data aggregation in WSNs is presented which includes techniques, tools, methodology and challenges in data aggregation. The literature covered fifteen types of data aggregation techniques in WSNs. Detailed analysis of this research work will help researchers to find the important characteristics of data aggregation techniques and will also help to select the most suitable technique for data aggregation. Research issues and future research directions have also been suggested in this research literature.

Tree based energy efficient routing scheme for body area network

Evolution of technology and day by day advancements in telecommunication, wireless communication, wireless sensors, and other technologies has led to development of such miniaturized sensors which can be implanted in or on the human body. This innovative and exhilarating area of research is Wireless Body Area Network (WBAN). Low power consumption and reliable data transmission is primary requirement in medical systems using WBAN. In this paper, we firstly explore efficient routing algorithm for WBAN and then it is modified to add energy factor with respect to routing gradient, energy aware expected transmission. Energy Efficient Tree Routing (EETR) algorithm is proposed for WBAN and it is compared with Ad-hoc On Demand Distance Vector Routing (AODVR) algorithm. This algorithm can jointly address the issue of low-power consumption and end-to end delay for reliable data transmission by modifying current algorithm so that nodes can robustly choose routing paths by minimizing the power levels for transmission. Considerable experiments are conducted using OMNET++ 4.5 as environment to ensure the successful implementation of proposed EETR algorithm by measuring number of factors like power consumption and Packet Reception Ratio (PRR). Experimental result analysis shows that EETR algorithm is beneficial than AODVR algorithm for energy efficient health monitoring using WBANs. In particular, single hop star topology and tree based multi-hop tree topology is compared with the help of extensive experiments conducted.

QoS Constraints Multicast Routing for Residual Bandwidth Optimization using Evolutionary Algorithm

For the real time multimedia applications, the routing algorithms should be designed to avoid congestion and to ensure data delivery within specified bounds. This paper presents an approach based on an evolutionary algorithm to solve the QoS constraint multicast routing problem. The proposed approach maximizes residual bandwidth utilization while satisfying end-to-end delay and delay jitter bounds. In the proposed algorithm, the encoding for generation of multicast trees is done by employing the topological features which ensure faster and guaranteed convergence. The effectiveness of the proposed algorithm is tested through the simulated results on various weighted networks.

Delay Bound Multicast Routing Using Hopfield Neural Network

The multicasting is used to transfer data from one or more sources to a potentially large number of destinations such that overall utilization of resources is minimized in some sense. An approach based on neural network is presented to solve the delay constraint multicast routing problem, which is a NP complete problem,. The multicast tree is obtained corresponding to optimum (minimum) routing cost subjected to end-to-end delay constraints. The multicast tree is obtained by recursively obtaining the delay bound shortest paths from source to various destinations and combining them by union operator to ensure that a link is appearing only once in the multicast tree. The effectiveness of the developed algorithm is tested to obtain optimum multicast trees for different sets of source and destinations on 14-node weighted connected network.

School bus routing based on branch and bound approach

Congestion in the traffic is the most basic problem that most of the cities facing now a days. This problem is mainly evolved due to increase in travel demand and limited scope of increasing the infrastructure needed to hold that traffic. So from there comes the concept of vehicle routing problem and thus the problem of School Bus Routing Problem (SBRP). In the past Hungarian Algorithm was used. Evolution of technology and day by day advancements in wireless communication and algorithms has lead us to use of Branch and Bound approach to solve this problem. In this paper, we explore efficient routing algorithm for SBRP. In, this paper, Branch and Bound Routing algorithm is proposed for SBRP. The Branch and bound algorithm provide optimal solution for the smaller problems. For a group of schools it will provide an optimal solution that will help those schools to optimize the bus routes, number of buses used and thus optimizing cost. This will also help in reducing pollution as the distance travelled by buses is optimized.

Hybrid Genetic Fuzzy Rule Based Inference Engine to Detect Intrusion in Networks

With the drastic increase in internet usage, various categories of attacks have also evolved. Conventional intrusion detection techniques to counter these attacks have failed and thus substantial systems are needed to eliminate these attacks before they inflict huge damage. With the ability of computational intelligence systems to adapt, exhibit fault tolerance, high computational speed and error resilience against noisy information, a hybrid genetic fuzzy rule based inference engine has been designed in this paper. The fuzzy logic constructs precise and flexible patterns while the genetic algorithm based on evolutionary computation helps in attaining an optimal solution, thus their collaboration will increase the robustness of intrusion detection system. The proposed network intrusion detection system will be able to classify normal behavior as well as anomalies in the network. Detailed analysis has been done on DARPA-KDD99 dataset to specify the behavior of each connection.

Tree structured encoding based multi-objective multicast routing algorithm

Quality-of-service (QoS) based multicast routing is a major challenge to next generation networks due to the increasing demand of real-time applications which require strict QoS guarantee. In the presented multi-objective multicast routing, the QoS parameters, namely, cost and available bandwidth are represented as objectives, while end-to-end delay and delay jitter are represented as constraints. The optimization is strived using an elitist multi-objective evolutionary algorithm. The topological assisted tree structured encoding was proposed to represent the multicast tree. The individual solution or chromosome was represented as a combination of arrays where each array represents a random route from destination node in multicast group to source node. The effectiveness of the proposed algorithm is tested on various networks, including the network formed using network topology generator BRITE. The best compromise solution is obtained using fuzzy cardinal priority ranking. The performance of this algorithm was compared with weighted sum genetic algorithm. The simulation results demonstrate that the multi-objective optimization with the proposed encoding scheme is effective in providing faster and guaranteed convergence.

Performance Comparison of Routing Protocols of MANET in Real World Scenario using NS3

Mobile ad hoc network (MANET) is an autonomous system of portable nodes connected by wireless links without using any need for centralized administration. Due to limited transmission range, each node acts as an end system and acts as a router to transmit the packets to destination hop by hop. MANET has certain characteristics like dynamic topology, limited bandwidth, CPU capacity, storage capacity, link failure and energy constraints, which imposes new demands on routing protocol. Each protocol operates differently in different network scenarios. MANET is not popularly used in every day applications, as all the simulations are done on non-real world scenarios. So this paper presents comparisons of AODV, DSDV and OLSR protocols in a real world scenario. Further, simulations are carried out using ns-3 network simulator.

Energy-efficient load balancing scheme for two-tier communication in wireless sensor networks

Wireless sensor network (WSN) has gained an enormous attention of researchers with its dynamic applications. Energy is considered as a scarce and the most vital resource in WSNs. In clustering-based approach, there is huge energy consumption while communicating data from cluster to base station (BS) and from sensor nodes to cluster head within a cluster. The repetitive use of same nodes and paths can result in network hole problem and service unavailability. There are number of research areas which have addressed the issues of energy efficiency and service availability. Load balancing is considered as one of the key techniques which are used to balance the trade-off between energy efficiency and service availability. In this research work, a novel real-time energy efficient load balancing technique for two-tier communication is proposed in which, initially in Tier 1, the energy consumption is reduced for communication between cluster to BS by applying space-time block coding over M-ary quadrature amplitude modulation and binary phase-shift keying modulations. In Tier 2, within a cluster, the energy consumption of communication among sensor nodes and CHs is reduced by utilizing the concepts of feedback control system, in which there is no need of the knowledge of static traffic demands. The performance of the proposed technique has been compared with the existing techniques in terms of energy utilization variation with varying order of transmit diversity and varying cluster BS distances, optimization of constellation sizes, energy utilization variation with cluster–BS distances for varying maximum link utilization and data rates along with varying traffic distribution and topology.