In a server/client system, a plurality of servers (101a, 101b to 101n) are connected to a client (102) via a network and according to a process request from the client (102), process executing servers (101b to 101n) execute processes and transmits the execution result to the client (102). A load distribution device (101a) includes a process information reception section (401) for receiving information on a process from the client (102), a decision section (402) for deciding a server to execute the process among the plurality of process executing servers (101b to 101n), and a server information transmission section (403) for transmitting the information on the decided server to the client (102). The client (102) includes a server information reception section (412) for receiving the transmitted information on the server and a process request transmission section (413) for transmitting information on a process executing request to the process executing servers (101b to 101n) associated with the received information.

Server/client system, load distribution device, load distribution method, and load distribution program

A communications system may include a plurality of servers connected together in a network, such as a wide area network (WAN). The servers may be for processing a plurality of different job types having respective different resource usage characteristics associated therewith. Moreover, each server may determine a respective health metric thereof based upon at least one job being processed thereby. Furthermore, each server may also weight the health metric based upon the respective resource usage characteristic of the at least one job. The system may also include a dispatcher for collecting the weighted health metrics from the servers and distributing jobs to the servers based thereon.

Communications system providing server load balancing based upon weighted health metrics and related methods

The original Linda model of coordination has always been attractive due primarily to its simplicity, but also due to the model’s other strong features of orthogonality, and the spatialand temporaldecoupling of concurrent processes. Recently there has been a resurgence of interest in the Linda coordination model, particularly in the Java community. We believe that the simplicity of this model still has much to offer, but that there are still challenges in overcoming the performance issues inherent in the Linda approach, and extending the range of applications to which it is suited. Our prior work has focused on mechanisms for generalising the input mechanisms in the Linda model, over a range of different implementation strategies. We believe that similar optimisations may be applicable to other aspects of the model, especially in the context of middleware support for components utilising web-services. The outcome of such improvements would be to provide a simple, but highly effective coordination language, that is applicable to a wide range of different application areas.

/pdf/coordination-languages-back-to-the-future-with-linda-2a0z7izcec.pdf

Coordination Languages: Back to the Future with Linda

Load balancing in distributed computer systems is t he process of redistributing the work load among proce ssors in the system to improve system performance. Most of previ ous research in using fuzzy logic for the purpose of load balancing has only concentrated in utilizing fuzzy logic concepts in d escribing processors load and tasks execution length. The res ponsibility of the fuzzy-based load balancing process itself, however, has not been discussed and in most reported work is assumed to b e performed in a distributed fashion by all nodes in the network. Th is paper proposes a new fuzzy dynamic load balancing algorithm for homo genous distributed systems. The proposed algorithm utiliz es fuzzy logic in dealing with inaccurate load information, making lo ad distribution decisions, and maintaining overall system stability . In terms of control, we propose a new approach that specifies h ow, when, and by which node the load balancing is implemented. Our approach is called Centralized-But-Distributed (CBD). Keywords—Dynamic load balancing, fuzzy logic, distributed systems, algorithm.

A Fuzzy Dynamic Load Balancing Algorithm for Homogenous Distributed Systems

Load balancing is essential for efficient utilization of resources and enhancing the responsiveness of a computational grid, especially that hosts of services most frequently used, i.e. food, health and nutrition. Various techniques have been developed and applied; each has its own limitations due to the dynamic nature of the grid. Efficient load balancing can be achieved by an effective measure of the node’s/cluster’s utilization. In this paper, as a part of an NSTIP project # 10-INF1381-04 and in order to assess of FAQIH framework ability to support the load balance in a computational grid that hosts of food, health and nutrition inquire services. We detail the design and implementation of a proposed fuzzy-logic-based scheme for dynamic load balancing in grid computing services. The proposed scheme works by using a fuzzy logic inference system which uses some metrics to capture the variability of loads and specifies the state of each node per a cluster. Then, based on the overall nodes’ states, the state of the corresponding cluster will be defined in order to assign the newly arrived inquires such that load balancing among different clusters and nodes is accomplished. Many experiments are conducted to investigate the effectiveness of the proposed fuzzy-logic-based scheme to support the load balance where the results show that the proposed scheme achieves really satisfactory and consistently load balance than of other randomize approaches in grid computing services.

/pdf/fuzzy-logic-based-scheme-for-load-balancing-in-grid-services-1cfvsqv7m9.pdf

Fuzzy Logic-Based Scheme for Load Balancing in Grid Services

A new fuzzy-decision based load balancing system for distributed object computing

Distributed object computing systems are widely envisioned to be the desired distributed software development paradigm in the near future due to the higher modularity and the capability of handling machine and operating system heterogeneity. Indeed, enabled by the tremendous advancements in processor and networking technologies, complex operations such as object serialization and data marshalling become very efficient, and thus, distributed object systems are being built for many different applications. As the system scales up (e.g., with larger number of server and client objects, and more machines), a judicious load balancing system is required to efficiently distribute the workload (e.g., the queries, messages/objects passing) among different servers in the system. Several such load balancing schemes are proposed recently in the literature. However, while the rationales and mechanisms employed are dramatically different, the relative strengths and weaknesses of these approaches are unknown, making it difficult for a practitioner to choose an appropriate approach for the problem at hand. In this paper, we describe in detail three representative approaches, which are all practicable, and present a quantitative comparison using a real experimental distributed object computing platform. Among these three approaches, namely, JavaSpaces based, request redirection based, and fuzzy decision based, we find that the fuzzy decision-based algorithm outperforms the other two considerably under a wide range of different practical scenarios.

On Load Balancing Approaches for Distributed Object Computing Systems

In this paper, we describe the design and implementation of a dynamic fuzzy-decision based load balancing system incorporated in a distributed object computing environment. The proposed approach works by using a fuzzy logic controller which informs a client object to use the most appropriate service such that load balancing among servers is achieved. We have chosen Jini to build our experimental middleware platform, on which our proposed approach as well as other approaches are implemented and compared. Extensive experiments are conducted to investigate the effectiveness of our fuzzy-decision based approach, which is found to be consistently better than other approaches.

The design and performance of an intelligent Jini load balancing service

Distributed object computing (DOC) environments are widely considered as important platforms for building practical network computing applications. To efficiently manage such environments, a load balancing technique can be applied to balance system processing load among multiple server hosts. However, due to the global state uncertainty, there is no suitable mathematical model to characterize network behavior such that accurate task placement decision can be predicted. Fuzzy logic is one of the most powerful paradigms in solving problems that are difficult to model mathematically. The design and implementation of a dynamic fuzzy load balancing service running in a DOC environment is described. We have chosen Jini (Sun Microsystems) as our experimental platform on which our proposed approach and random and round-robin approaches are implemented and compared.

A fuzzy approach to load balancing in a distributed object computing network

Distributed object computing systems are widely envisioned to be the desired distributed software development paradigm due to the higher modularity and the capability of handling machine and operating system heterogeneity. As the system scales up (e.g., with larger number of server and client objects, and more machines), a judicious load balancing system is required to efficiently distributed the workload (e.g., the queries, messages/objects passing) among the different servers in the system. However, in existing distributed object middleware systems, such a load balancing facility is lacking. In this paper, we describe the design and implementation of a dynamic fuzzy-decision based load balancing system incorporated in a distributed object computing environment. The proposed approach works by using a fuzzy logic controller which informs a client object to use the most appropriate service such that load balancing among servers is achieved. We have chosen Jini to build our experimental middleware platform, on which our proposed approach as well as other approaches are implemented and compared. Extensive experiments are conducted to investigate the effectiveness of our fuzzy-decision based approach, which is found to be consistently better than other approaches.

/pdf/a-fuzzy-load-balancing-service-for-network-computing-based-10za0dh1rx.pdf

A Fuzzy Load Balancing Service for Network Computing Based on Jini

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