Ailixier Aikebaier

A Model for Reducing Power Consumption in Peer-to-Peer Systems

Information systems based on the cloud computing model and peer-to-peer (P2P) model are now getting popular. In the cloud computing model, a cloud of servers support thin clients with various types of service like Web pages and databases. On the other hand, every computer is peer and there is no centralized coordinator in the P2P model. It is getting more significant to discuss how to reduce the total electric power consumption of computers in information systems to realize eco-society. In this paper, we consider a Web type of application on P2P overlay networks. First, we discuss a model for showing how much each server peer consumes electric power to perform Web requests from client peers. Then, we discuss algorithms for a client peer to select a server peer in a collection of server peers so that the total power consumption can be reduced while some constraint like deadline one is satisfied. Lastly, we evaluate the algorithms in terms of the total power consumption and throughput compared with traditional round robin algorithms.

Process Allocation Algorithms for Saving Power Consumption in Peer-to-Peer Systems

Information systems are composed of various types of computers interconnected in networks. In addition, information systems are being shifted from the traditional client-server model to the peer-to-peer (P2P) model. P2P systems are scalable and fully distributed without any centralized coordinator. Here, it is getting more significant to discuss how to reduce the total electric power consumption of computers in addition to developing distributed algorithms to minimize the computation time and memory space. In this paper, we do not discuss microlevel models like the hardware specifications of computers like low-energy CPUs. We rather discuss a macrolevel model to show the relation of the amount of computation and the total power consumption of multiple peer computers to perform Web types of application processes. We also discuss algorithms for allocating a process to a computer so that the deadline constraint is satisfied and the total power consumption is reduced.

An Extended Simple Power Consumption Model for Selecting a Server to Perform Computation Type Processes in Digital Ecosystems

In information systems, applications are required to be realized in the digital ecosystems, high performance systems, and scalable systems. In these applications, a client first selects a server in a cluster of servers and issues a request to the server. The request is performed as a process in the server. In this paper, we consider a computation process which mainly consumes the central processing unit (CPU) resources. Cooling devices, such as fans, consume the electric power in addition to the CPU of a server. The rotation speed of a fan is revved up in servers in order to decrease the temperature of a server. Thus, the total power consumption of a server depends on not only computational devices such as a CPU, but also cooling devices. We discuss an extended simple power consumption (ESPC) model of a server with a multicore CPU and cooling devices to perform computation type processes. It is critical to discuss how to select a server for each request issued by a client in order to not only achieve performance objectives, but also reduce the total power consumption of a system based on the ESPC model. An improved power consumption laxity-based (IPCLB) algorithm for selecting a server is proposed in this paper, where the minimum power to be consumed is used to perform the process. We evaluate the ESPC model and IPCLB algorithm in terms of power consumption and elapse time.

Power Consumption-Based Server Selection Algorithms for Communication-Based Systems

We have to reduce the total electrical power consumption in information systems. In this paper, we consider communication based applications where a server transmits a large volume of data to a client like file transfer protocol (FTP). We discuss a power consumption model for communication-based applications, where the total power consumption of a server depends on the total transmission rate and number of clients where the server concurrently transmits files. A client has to select a server in a set of possible servers, each of which holds a file, so that the power consumption of the server is reduced. We evaluate a pair of PCB (power consumption-based) and TRB (transmission rate-based) algorithms to select a server. In the evaluation, we show the total power consumption can be reduced by the PCB and TRB algorithms compared with the traditional round-robin (RR) algorithm and PCB is more practical than TRB.

Trustworthy-based efficient data broadcast model for P2P interaction in resource-constrained wireless environments

In a decentralised system like P2P where each individual peers are considerably autonomous, the notion of mutual trust between peers is critical. In addition, when the environment is subject to inherent resource constraints, any efficiency efforts are essentially needed. In light of these two issues, we propose a novel trustworthy-based efficient broadcast scheme in a resource-constrained P2P environment. The trustworthiness is associated with the peer@?s reputation. A peer holds a personalised view of reputation towards other peers in four categories namely SpEed, Correctness, qUality, and Risk-freE (SeCuRE). The value of each category constitutes a fraction of the reliability of individual peer. Another factor that contributes to the reliability of a peer is the peer@?s credibility concerning trustworthiness in providing recommendation about other peers. Our trust management scheme is applied in conjunction with our trust model in order to detect malicious and collaborative-based malicious peers. Knowledge of trustworthiness among peers is used in our proposed broadcast model named trustworthy-based estafet multi-point relays (TEMPR). This model is designed to minimise the communication overhead between peers while considering the trustworthiness of the peers such that only trustworthy peer may relay messages to other peers. With our approach, each peer is able to disseminate messages in the most efficient and reliable manner.

Trustworthy Group Making Algorithm in Distributed Systems

Information systems are being shifted to scalable architectures like Cloud and peer-to-peer (P2P) models. In this paper, we consider the P2P model as a fully distributed, scalable system different from centralized coordinated systems in Cloud and Grid systems. A P2P system is composed of peer processes (peers). Here, applications are realized by activities of peers and cooperations among multiple peers. In P2P systems, since there is no centralized coordination, each peer has to obtain information about other peers by itself. In the group cooperation, each group member peer has to be trustworthy so that malicious behavior of a member peer cannot effect overall outcome of the whole group. Here, it is important to consider the trustworthiness of each group member as a base of an agreement procedure in the distributed environment. The goal of a group and the way to archive the goal are decided by the group members. During the agreement procedure, opinions of member peers have to be collected in a group. Malicious and unexpected behaviors of member peers can negatively effect the output of a group. Hence, it is significant to discuss how to compose a group only by including more trustworthy peers. In this paper, by taking advantage of the trustworthiness concept of each peer, we propose a novel approach to composing a trustworthy group in the distributed agreement protocols.

An Integrated Power Consumption Model for Communication and Transaction Based Applications

In order to realize digital ecosystems, the total electric power consumption of computers and networks have to be reduced. In distributed systems, clients issue requests to servers and then servers send replies to clients. Here, application processes are composed of a pair of modules which mainly consume computation and communication resources, respectively. Based on the measurement of the power consumption of a server, we newly discuss a power consumption model of a server for applications. We propose an EPCLB (extended power consumption laxity-based) algorithm to select one of servers for applications so that the total power consumption of servers can be reduced. We evaluate the EPCLB algorithm in terms of execution time and power consumption compared with the traditional round-robin algorithm.

Algorithms for Reducing the Total Power Consumption in Data Communication-Based Applications

It is now critical to reduce the consumption of natural resources, especially petroleum. Even in information systems, we have to reduce the total electrical power consumption. We classify network applications to two types of applications, transaction and communication based ones. In this paper, we consider communication based applications like the file transfer protocol (FTP). A computer named server consumes the electric power to transfer a file to a client depending on the transmission rate. We discuss a model for power consumption of a data transfer application which depends on the total transmission rate and number of clients to which the server concurrently transmits files. A client has to find a server in a set of servers, each of which holds a file so that the power consumption of the server is reduced. We discuss a pair of algorithms PCB (power consumption-based) and TRB (transmission rate-based) to find a server which transmits a file to a client. In the evaluation, we show the total power consumption can be reduced by the algorithms compared with the traditional round-robin algorithm.

Energy-Efficient Computation Models for Distributed Systems

Information systems are composed of various types of computers interconnected in types of networks like wireless networks. In addition, information systems are being shifted from the traditional client-server model to the peer-to-peer (P2P) model. The P2P systems are composed of peer processes (peers). They are scalable and fully distributed without centralized coordinators. It is getting more significant to discuss how to reduce the total energy consumption of computers in information systems in addition to developing algorithms to minimize the computation time and memory size. Low-energy CPUs and storage devices like SSD are now being developed at architecture level. In this paper, we do not discuss the hardware specification of each computer. We discuss how to reduce the total energy consumption of multiple peer computers to perform types of programs on P2P overlay networks at macro level. We propose models for realizing energy-efficient computation in P2P systems. We also discuss an allocation algorithm of a process to a peer computer so that the deadline constraint is satisfied and the total energy consumption is reduced.

Reliable Message Broadcast Schemes in Distributed Agreement Protocols

Nowadays information systems are being shifted to distributed architectures. The peer-to-peer (P2P) model as a fully distributed system, is composed of peer processes (peers). Here, peers have to efficiently and flexibly make an agreement on one common value which satisfies an agreement condition. In the agreement protocol, each peer has to deliver values to all the peers in a group. We take advantage of the multipoint relaying (MPR) mechanism to efficiently broadcast messages. Here, if a peer which forwards messages to other peers is faulty, the peers cannot receive messages. In this paper, we newly discuss a trustworthiness-based broadcast (TBB) algorithm where only the trustworthy peers forward messages. That is, untrustworthy peers, i.e. peers prone to faults and malicious behaviors do not forward messages. Here, the transmission fault implied by faulty peers can be reduced. We evaluate the TBB algorithm in terms of the number of messages compared with the pure flooding and MPR algorithms.