R. Asokan

A swarm-based hybrid routing protocol to support multiple Quality of Service (QoS) metrics in mobile ad hoc networks

Quality of Service support in routing for Mobile Ad hoc Networks (MANETs) is a challenging process because of the limitation on available resources and the dynamic topology. The main purpose of QoS routing is to find a feasible path that has sufficient resources to satisfy the constraints. A fundamental problem in QoS routing is to find a path between a source and destination that satisfies two or more end-to-end QoS constraints/metrics. Considering more than two metrics involves more computational complexity and it is proved to be NP-complete problem. Stochastic optimization techniques are better solutions for these kinds of problems. A routing model can be chosen either as proactive or reactive. Purely proactive protocols are not optimal for rapidly changing topologies and purely reactive protocols are often inappropriate for relatively static networks. In addition, reactive protocols also suffer with additional delay for real-time traffic. In such scenarios, hybrid routing is proven to improve on purely reactive-routing or purely proactive-routing if most traffic is localized. In order to achieve routing efficiency in such environment, a hybrid routing strategy is proposed which combines the advantages of both proactive and reactive mechanisms. In this paper, a novel QoS routing strategy called Swarm-based Hybrid Routing Protocol (SHRP) based on ant colony optimization is proposed to support the three metrics such as end-to-end delay, bandwidth and hop count. To evaluate the performance of SHRP, a series of simulations are carried out with the simulator QualNet. The simulation results of SHRP are compared with the hybrid routing protocols ZRP and HOPNET. Through the simulation results, it has been showed that SHRP fabricates better performance than ZRP and HOPNET in terms of packet delivery ratio, throughput, end-to-end delay, bandwidth and hopcount.

Distributed Denial of Service (DDOS) Attacks Detection Mechanism

Pushback is a mechanism for defending against Distributed Denial-of-Service (DDoS) attacks. DDoS attacks are treated as a congestion-control problem, but because most such congestion is caused by malicious hosts not obeying traditional end-to-end congestion control, the problem must be handled by the routers. Functionality is added to each router to detect and preferentially drop packets that probably belong to an attack. Upstream routers are also notified to drop such packets in order that the routers resources be used to route legitimate traffic hence term pushback. Client puzzles have been advocated as a promising countermeasure to DoS attacks in the recent years. In order to identify the attackers, the victim server issues a puzzle to the client that sent the traffic. When the client is able to solve the puzzle, it is assumed to be authentic and the traffic from it is allowed into the server. If the victim suspects that the puzzles are solved by most of the clients, it increases the complexity of the puzzles. This puzzle solving technique allows the traversal of the attack traffic throughout the intermediate routers before reaching the destination. In order to attain the advantages of both pushback and puzzle solving techniques, a hybrid scheme called Router based Pushback technique, which involves both the techniques to solve the problem of DDoS attacks is proposed. In this proposal, the puzzle solving mechanism is pushed back to the core routers rather than having at the victim. The router based client puzzle mechanism checks the host system whether it is legitimate or not by providing a puzzle to be solved by the suspected host.

Maximum Power Point Tracking of Modified Three Level Boost Converter for Thermo Electric Generator using Fuzzy Logic

Energy harvesting is one of the important issues so as to meet certain small percentage of energy requirements in industries. Thermo electric generator is a Waste heat recovery system, which utilizes the waste heat from boilers exhaust system in a unit, engine exhaust etc and can be utilized to generate power so as to run many loads. The thermo electric generator works on the principle of seebeck effect, the seebeck effect is the conversion of temperature difference directly into electricity. In this proposed work the TEG output source is used to charge the battery and it used to operate the load as and when required to operate any loads. In this the output of the TEG is regulated by boost converter. The boost converter is controlled by an intelligent controller namely fuzzy controller, which is easy to implement and it produces precise output. Thus this proposed model using fuzzy controller boost converter is controlled and boost converters are used to increase conversion efficiency and output power up to 120w is obtained in the simulation and it can be used for operating medical server which is meant for monitoring of health of plant operators in the industry in which abundant exhaust heat is available for being used.

Performance Evaluation of Weighted Round Robin Grid Scheduling

Grid systems interconnect heterogeneous and geographically distributed resources to form a network which satisfy user’s needs. Resource Management is its central component and involves managing system resources. It is responsible for accepting user’s requests and matching it to available resources which can be accessed by the user. Schedulers are applications which manage jobs including allocating resources for specific jobs. When there are many processes in a queue, the order in which jobs are executed is decided by a scheduling algorithm. This paper proposes and investigates the performance of varied task execution for proposed weighted round robin scheduling algorithm. Simulations evaluate the proposed method’s performance and results demonstrate that the proposed method performs satisfactorily.

Impact of node density on the performance of ad hoc routing protocols

An ad hoc network comprises of mobile computing devices that use wireless transmission for communication. It has no fixed infrastructure. The mobile devices also serve as routers. Ad hoc wireless networks can be deployed quickly anywhere and anytime as they eliminate the complexity of infrastructure setup. It finds applications in military communications, emergency operations, hybrid wireless network architectures and wireless mesh networks. A variety of routing protocols for ad hoc networks has been proposed in the past. The routing protocols are broadly classified into Proactive, Reactive and Hybrid protocols. This paper evaluates the performance of FSR (Proactive), AODV (Reactive) and ZRP (Hybrid) routing protocols using qualnet simulator.