Cloud Computing offers indispensable infrastructure for storage and computing facilities for development of diversified services. The large utilization of resources leads to increased energy consumption that has imposed a limit on performance growth. Owing to high operational costs and carbon dioxide footprints, an efficient energy management technique needs to be developed and deployed that reduces overall energy consumption of a cloud environment while maximizing the resource utilization. In the first phase of this research, some virtual machine migration techniques were explored. In the second phase, a virtual machine migration technique has been implemented which aims at reducing energy consumption in cloud datacentres. General TermsVirtual Machine Migration, Bin Packing Algorithms.

In this paper, we describe the approaches for routing in Wireless Sensor Networks. Their characteristics are discussed. An efficient routing approach is then proposed using genetic algorithm which is based on energy equations and use of advanced nodes having high energy than normal nodes. This intelligent cluster routing is then compared with SEP routing.

Due to significant advancement in wireless communication, wireless sensor networks (WSNs) have attracted great attention in recent years. WSNs are randomly deployed, battery operated autonomous systems consisting of large number of sensors nodes which are responsible for transmitting the real-time sensed data for a specific application in the monitoring area to the base station where it can be further processed and analyzed. However, due to wireless communication, the network is easily compromised. Solutions dedicated to wire networks are not suited in the resource constrained wireless network. There is still a scope for wide research potential in the field of wireless sensor network security. In this paper, we analyzed the issues related to security in WSNs and also highlight the research area in the field of wireless sensor networks.

Vehicle Routing Problem with Time Window (VRPTW), an extension of VRP, is a complex combinatorial problem having many real life applications. It can be described as the problem of minimizing the total route cost while satisfying the capacity and time window constraint. Ant Colony System (ACS) is a meta heuristic that is often applied to solve VRPTW. In this paper an attempt has been made to enhance the already existing ant colony system to solve the problem efficiently. Experimentation with the Solomon data sheet is performed and compared with best known results available in literature.

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Designing an energy efficient key management scheme to secure Wireless Sensor Networks is a challenging task because sensor nodes in the network are resource constrained. If an initial key is used in the network lifetime, a key stolen by an unauthorized node will results in data compromised that is generated in the network. So a re-keying is necessary after a specified number of rounds to avoid the side effect of stale key in the network. In clustering environment, a number of keys are needed for every sensor. If the role of sensor is cluster head, then one key is required to collect data from all cluster members. This key is shared between the cluster head sensor and all the sensors which are members of that cluster. The different key is required to transfer the aggregated data to base station this key is only shared between the sensor node which is cluster head and the base station. But if the role of cluster head is changed from one sensor to different sensor randomly, a new key will be require that is share between sensor node and new cluster head and also a new key will be required that is shared between this new cluster head and the base station. If the scheme is followed then rekeying after every round is a bottleneck of the network as more than one re-keying is require for every sensor. In this paper, we have presented a new virtual location based key management scheme (VLKM). This scheme used virtual location to generate a round key for every sensor. Simulation results show that proposed scheme performs better than other comparable schemes in the literature without increasing the communication overheads.

Abstract-Cloud paradigm is an embryonic computing model that in its vicinity stresses on proficient utilization of computing resources. Data centers that host and service cloud applications ingest enormous amount of energy, leading to massive emission of carbon footprints to the atmosphere and high operational expenditures. Consequently, there is a need to establish synergy between data centre resources for optimum resource utilization and strategies needs to be devised that can considerably reduce energy consumption in cloud data center. This paper elucidates an architectural framework for computation of energy spent in scheduling resources on hosts. The framework has been implemented for bin-packing techniques and explicates minutiae about broker components involved in scheduling process. Keyword-Cloud Computing, Energy Consumption, VM Migration, Resource Scheduling.I. INTRODUCTION Contemporary [1,2] resource-intensive enterprises has engendered demands for high performance computing infrastructures. Proliferation of IT services to be used by diverse range of cloud users has led to construction of large-scale energy hungry data centers that can facilitate computing services. Despite of the improvisations introduced in energy consumption models, service providers are confronted with challenges of reduction in energy consumption and CO 2 emission.The rationale [3] in the wake of explosion of energy emission is increase in number of computer usage due to increase in number of IT practitioners. As an upshot, size of data centres has increased. Moreover, exploiting energy-aware resource provisioning to its fullest extent can subsequently provide a solution to the forefront issues.[4] Service virtualization and consolidation are acting as inherent practices that can escort energyefficient datacenter architectures. It has effectually led to efficient resource utilization. VM provisioning can be sighted as a multidimensional bin packing problem comprising of capricious bin configurations and cost parameters. Virtualization technique embraces server consolidation process and a VM live-migration technique that has validated to be efficient in drastic reduction in energy consumption in high-performance cloud datacenters. However, I/O virtualization has excavated grounds for performance degradation posed by overheads encountered in vm migrations and needs to be addressed urgently.The organization of paper is laid out as literature review in beginning followed by research focus. The IV section elucidates architectural framework trailed by working prototype. The last section illustrates conclusion and future work.II. LITERATURE REVIEW The research work presented in [5] explores method to manage data intensive distributed programming paradigms (like MapReduce and Dryad) that assists practitioners to effortlessly parallelize the processing of huge data sets. Deployment of such data intensive computing infrastructures is of significant concern due to rise in cost. The work carried out in the study dynamically adjusts the size ...

A web page which is a source of information consist lots of parts among which only a part of the information is useful for a particular application and the remaining information are noises. An effective technique for users to extract the useful information from the total information is urgently required. Hence by removing those noise patterns from the web page, the efficiency of the web data extraction can be improved. This research work propose an approach for removing the local noise from a given web page based on n x 1 table and XSL display method with filter feature for improving the efficiency of web data extraction.