Cluster Based Distributed Service Discovery in Internet of Vehicle

As automobile sector is witnessing a paradigm shift from Internal Combustion Engine (ICE) based vehicles to smart electric vehicles, a new concept of connected vehicles has emerged that is able to provide a number of services to its users. Internet of Vehicles has now transformed to an indispensable platform of information exchange among vehicles, city infrastructure, drivers and other connected entities. Due to highly dynamic nature of Internet of Vehicles, there is need of a dynamic service discovery infrastructure that can cater to Internet of Vehicle specific challenges. This paper is a step ahead in that direction to provide a distributed service discovery protocol that facilitates service discovery and service selection for Internet of Vehicles environment. We have proposed a clustering based service discovery approach that makes use of neighbor awareness to find neighboring vehicles. Proposed protocol has been validated by running extensive simulations and results show the improvement in terms of query success rate, transmission rate and transmission cost by a considerable margin

QoS Aware Service Scheduling Scheme for VANETs

People immediately want to access the required data in vehicular ad hoc networks (VANETs). They provide the requests to road side unit (RSU) while travelling. The job of RSU is to handle various requests in such a way so that the service ratio and the quality of service (QoS) is optimized. In this paper we present a mechanism to achieve this goal. Our proposed algorithm considers both data size and deadline and optimizes uploading/downloading based on number of requests to be handled. It also deals with the impact of missed upload operations to achieve maximum optimization. The proposed scheme categorizes data into two classes to assign weight according to their effect on QoS and assigns priorities to upload and download requests while maintaining common queue for both upload and download requests. Simulation results corroborate that the proposed algorithm provides better service ratio and QoS than existing techniques

Cooperative Caching in Mobile Ad Hoc Networks Based on Data Utility

Cooperative caching, which allows sharing and coordination of cached data among clients, is a potential technique to improve the data access performance and availability in mobile ad hoc networks. However, variable data sizes, frequent data updates, limited client resources, insufficient wireless bandwidth and client's mobility make cache management a challenge. In this paper, we propose a utility based cache replacement policy, least utility value (LUV), to improve the data availability and reduce the local cache miss ratio. LUV considers several factors that affect cache performance, namely access probability, distance between the requester and data source/cache, coherency and data size. A cooperative cache management strategy, Zone Cooperative (ZC), is developed that employs LUV as replacement policy. In ZC one-hop neighbors of a client form a cooperation zone since the cost for communication with them is low both in terms of energy consumption and message exchange. Simulation experiments have been conducted to evaluate the performance of LUV based ZC caching strategy. The simulation results show that, LUV replacement policy substantially outperforms the LRU policy

A New Approach Layered Architecture based Clustering for Prolong Life

ABSTRACT 1.INTRODUCTION Low cost inexpensive sensors which are capable of significant computation are become available RELATED WORK LEACH is based on the fusion (or aggregation) technique which combines the original data into the smaller size of data and carries only meaningful information to all the sensor nodes 3.PROBLEM STATEMENT When the network is first time deployed, the energy of all the nodes is same. As the network starts functioning, few nodes lose their energy faster and die earlier as compare