• Energy Research

Energy conservation is a critical issue in battery powered mobile nodes of mobile ad hoc networks (MANETs). Most MANETs routing protocols use some form of flooding to discover routes among mobile nodes. Despite various optimizations, many route discovery messages are still propagated without considering a coalesce effect of node density and residual energy. During route discovery process, each node of MANET should not blindly broadcast because malfunction of node or link might occur and allows establishing a new path from source to destination which creates extra energy consumption of nodes, sparse network density and a more likelihood occurrence of network partition. In this paper we are developing and evaluating an energy aware routing protocol called a gossip based balanced battery usage routing protocol (GBBU) which integrates minimum residual energy and node degree as cost metric to minimize and distribute energy consumption of MANETs based on Ad hoc on demand distance vector (AODV). The performance of the protocol is measured based on reachability, energy consumed per packet delivered, delivery ratio, average end-to-end delay, and network lifetime using network simulator-2.35. The simulation results show that GBBU routing protocol minimizes energy consumption per packet and fairly distribute energy usage across mobile nodes.

This paper proposes an agent based approach to the scheduling of jobs in data centers under thermal constraints. The model encompasses both temporal and spatial aspects of the temperature evolution using a unified model, taking into account the dynamics of heat production and dissipation. Agents coordinate to eventually move jobs to the best suitable place and to adapt dynamically the frequency settings of the nodes to the best combination. Several objectives of the agents are compared under different circumstances by an extensive set of experiments.

Datacenters have become an important part of todays computing infrastructure. Recent studies have shown the increasing importance of thermal considerations to achieve effective resource management. In this paper, we study thermal-aware scheduling for homogeneous high-performance computing (HPC) datacenters under a thermal model that captures both spatial and temporal correlations of the temperature evolution. We propose an online scheduling heuristic to minimize the makespan for a set of HPC applications subject to a thermal constraint. The heuristic leverages the novel notion of thermal-aware load to perform both job assignment and thermal management. To respect the temperature constraint, which is governed by a complex spatio-temporal thermal correlation, dynamic voltage and frequency scaling (DVFS) is used to regulate the job executions during runtime while dynamically balancing the loads of the servers to improve makespan. Extensive simulations are conducted based on an experimentally validated datacenter configuration and realistic parameter settings. The results show improved performance of the proposed heuristic compared to existing solutions in the literature, and demonstrate the importance of both spatial and temporal considerations. In contrast to some scheduling problems, where DVFS introduces performanceenergy tradeoffs, our findings reveal the benefit of applying DVFS with both performance and energy gains in the context of spatio-temporal thermal-aware scheduling. Thermal model capturing both spatial and temporal temperature correlations in datacenters.Formulation of a spatio-temporal thermal-aware scheduling problem for HPC applications.Scheduling heuristic using thermal-aware load for job assignment and thermal management.Simulations to show the effectiveness of heuristic under a wide range of parameters.

This chapter presents the landscape of green information technology (IT), focusing on large‐scale distributed systems. First, it gives a definition of Green IT and its difference and links with sustainability. Then, the chapter outlines the differences in points of view for considering Green IT between academic and industry players. It describes the role of several actors: technology transfer office (TTOs), standardization bodies, industries, and researchers. The authors believe that three main reasons drive the interests for Green IT and its development: ecology, economy, and society. The chapter describes the different standardization bodies and some contextualized actions in the scope of large‐scale distributed systems, focusing mainly on the data center side. Finally, a modeling of the actors is proposed and its usage for helping decision makers is sketched.

Cloud computing is today’s most emphasized Information and Communications Technology (ICT) paradigm that is directly or indirectly used by almost every online user. However, such great significance comes with the support of a great infrastructure that includes large data centers comprising thousands of server units and other supporting equipment. Their share in power consumption generates between 1.1% and 1.5% of the total electricity use worldwide and is projected to rise even more. Such alarming numbers demand rethinking the energy efficiency of such infrastructures. However, before making any changes to infrastructure, an analysis of the current status is required. In this article, we perform a comprehensive analysis of an infrastructure supporting the cloud computing paradigm with regards to energy efficiency. First, we define a systematic approach for analyzing the energy efficiency of most important data center domains, including server and network equipment, as well as cloud management systems and appliances consisting of a software utilized by end users. Second, we utilize this approach for analyzing available scientific and industrial literature on state-of-the-art practices in data centers and their equipment. Finally, we extract existing challenges and highlight future research directions.

The question of energy savings has been a matter of concern since a long time in the mobile distributed systems and battery-constrained systems. However, for large-scale non-mobile distributed systems, which nowadays reach impressive sizes, the energy dimension (electrical consumption) just starts to be taken into account. In this paper, we present the GREEN-NET framework which is based on 3 main components: an ON/OFF model based on an Energy Aware Resource Infrastructure (EARI), an adapted Resource Management System (OAR) for energy efficiency and a trust delegation component to assume network presence of sleeping nodes.