Economic impact of energy saving techniques in cloud server

In recent years, lot of research has been carried in the field of cloud computing and distributed systems to investigate and understand their performance. Economic impact of energy consumption is of major concern for major companies. Cloud Computing companies (Google, Yahoo, Gaikai, ONLIVE, Amazon and eBay) use large data centers which are comprised of virtual computers that are placed globally and require a lot of power cost to maintain. Demand for energy consumption is increasing day by day in IT firms. Therefore, Cloud Computing companies face challenges towards the economic impact in terms of power costs. Energy consumption is dependent upon several factors, e.g., service level agreement, virtual machine selection techniques, optimization policies, workload types etc. We address a solution for the energy saving problem by enabling dynamic voltage and frequency scaling technique for gaming data centers. The dynamic voltage and frequency scaling technique is compared against non-power aware and static threshold detection techniques. This helps service providers to meet the quality of service and quality of experience constraints by meeting service level agreements. The CloudSim platform is used for implementation of the scenario in which game traces are used as a workload for testing the technique. Selection of better techniques can help gaming servers to save energy cost and maintain a better quality of service for users placed globally. The novelty of the work provides an opportunity to investigate which technique behaves better, i.e., dynamic, static or non-power aware. The results demonstrate that less energy is consumed by implementing a dynamic voltage and frequency approach in comparison with static threshold consolidation or non-power aware technique. Therefore, more economical quality of services could be provided to the end users

Bringing IPTV to the Market through Differentiated Service Provisioning

The world of telecommunications continues to provide radical technologies. Offering the benefits of a superior television experience at reduced long-term costs, IPTV is the newest offering. Deployments, however, are slow to be rolled out; the hardware and software support necessary is not uniformly available. This paper examines the challenges in providing IPTV services and the limitations in developments to overcome these challenges. Subsequently, a proposal is made which attempts to help solve the challenge of fulfilling real-time multimedia transmissions through provisioning for differentiated services. Initial implementations in Opnet are documented, and the paper concludes with an outline of future work

An Efficient Rerouting Approach in Software Defined Networks

This paper illustrates an efficient traffic rerouting solution in Software-Defined Networks (SDN) by monitoring the network status periodically. The proposed approach provides a rerouting solution by first calculating the link utilization for available paths and then rerouting the flow to the least delay path among the available paths. The traffic rerouting solution is considering the network condition to prevent the switch overutilization and congestion while any new flow arrives. The proposed method is implemented by using ONOS controller and Mininet emulator. The proposed algorithm in the controller predicts the utilization and delay on the link to calculate how much load to be rerouted if the average link utilization exceeds the threshold level. Hence, this method will proactively avoid congestion by adding flows, monitoring the parameters and prevent the unbalanced distribution after rerouting as our experimental results show

On the Study of Sustainability and Outage of SWIPT-Enabled Wireless Communications

Wireless power transfer technologies such as simultaneous wireless information and power transfer (SWIPT) have shown significant potential to revolutionise the design of future wireless communication systems. When the only energy source is from the wireless signals that are mainly intended for information communications, the sustainability and outage performance of SWIPT systems become critical factors in theoretical evaluation and practical applications. This paper firstly models the energy harvesting and energy consumption of the power splitting protocol based SWIPT systems to investigate the general sustainability condition. We further model the power and information transfer outage probabilities using Markov Chains, which are unique for SWIPT systems since they both could cause communication outage. We further demonstrate how to apply the closed-form expression of the outage to optimise the key parameter of splitting ratio for SWIPT systems. Hardware and numerical experiments demonstrate the validity of the proposed model and outage analysis, and confirm the effectiveness of the solution to calculate the optimal splitting ratios under different signal and channel conditions

A review on communication aspects of demand response management for future 5G IoT- based smart grids

In recent power grids, the need for having a two-way flow of information and electricity is crucial. This provides the opportunity for suppliers and customers to better communicate with each other by shifting traditional power grids to smart grids (SGs). In this paper, demand response management (DRM) is investigated as it plays an important role in SGs to prevent blackouts and provide economic and environmental benefits for both end-users and energy providers. In modern power grids, the development of communication networks has enhanced DRM programmes and made the grid smarter. In particular, with progresses in the 5G Internet of Things (IoT), the infrastructure for DRM programmes is improved with fast data transfer, higher reliability, increased security, lower power consumption, and a massive number of connections. Therefore, this paper provides a comprehensive review of potential applications of 5G IoT technologies as well as the computational and analytical algorithms applied for DRM programmes in SGs. The review holistically brings together sensing, communication, and computing (optimization, prediction), areas usually studied in a scattered way. A broad discussion on various DRM programmes in different layers of enhanced 5G IoT based SGs is given, paying particular attention to advances in machine learning (ML) and deep learning (DL) algorithms alongside challenges in security, reliability, and other factors that have a role in SGs’ performance

A Dynamic Approach to MIB Polling for Software Defined Monitoring

Technology trends such as Software-Defined Networking (SDN) are transforming networking services in terms of flexibility and faster deployment times. SDN separates the control plane from the data plane with its centralised architecture compared with the distributed approach used in other management systems. However, management systems are still required to adapt the new emerging SDN-like technologies to address various security and complex management issues. Simple Network Management Protocol (SNMP) is the most widespread management protocol implemented in a traditional Network Management System (NMS) but has some limitations with the development of SDNlike services. Hence, many studies have been undertaken to merge the SDN-like services with traditional network management systems. Results show that merging SDN with traditional NMS systems not only increases the average Management Information Base (MIB) polling time but also creates additional overheads on the network. Therefore, this paper proposes a dynamic scheme for MIB polling using an additional MIB controller agent within the SDN controller. Our results show that using the proposed scheme, the average polling time can be significantly reduced (i.e., faster polling of the MIB information) and also requires very low overhead because of the small sized OpenFlow messages used during polling