Muthucumaru Maheswaran

A Comparison of Eleven Static Heuristics for Mapping a Class of Independent Tasks onto Heterogeneous Distributed Computing Systems

Mixed-machine heterogeneous computing (HC) environments utilize a distributed suite of different high-performance machines, interconnected with high-speed links, to perform different computationally intensive applications that have diverse computational requirements. HC environments are well suited to meet the computational demands of large, diverse groups of tasks. The problem of optimally mapping (defined as matching and scheduling) these tasks onto the machines of a distributed HC environment has been shown, in general, to be NP-complete, requiring the development of heuristic techniques. Selecting the best heuristic to use in a given environment, however, remains a difficult problem, because comparisons are often clouded by different underlying assumptions in the original study of each heuristic. Therefore, a collection of 11 heuristics from the literature has been selected, adapted, implemented, and analyzed under one set of common assumptions. It is assumed that the heuristics derive a mapping statically (i.e., off-line). It is also assumed that a metatask (i.e., a set of independent, noncommunicating tasks) is being mapped and that the goal is to minimize the total execution time of the metatask. The 11 heuristics examined are Opportunistic Load Balancing, Minimum Execution Time, Minimum Completion Time, Min?min, Max?min, Duplex, Genetic Algorithm, Simulated Annealing, Genetic Simulated Annealing, Tabu, and A*. This study provides one even basis for comparison and insights into circumstances where one technique will out-perform another. The evaluation procedure is specified, the heuristics are defined, and then comparison results are discussed. It is shown that for the cases studied here, the relatively simple Min?min heuristic performs well in comparison to the other techniques.

A taxonomy and survey of grid resource management systems for distributed computing

The resource management system is the central component of distributed network computing systems. There have been many projects focused on network computing that have designed and implemented resource management systems with a variety of architectures and services. In this paper, an abstract model and a comprehensive taxonomy for describing resource management architectures is developed. The taxonomy is used to identify approaches followed in the implementation of existing resource management systems for very large‐scale network computing systems known as Grids. The taxonomy and the survey results are used to identify architectural approaches and issues that have not been fully explored in the research. Copyright

Dynamic Mapping of a Class of Independent Tasks onto Heterogeneous Computing Systems

Dynamic mapping (matching and scheduling) heuristics for a class of independent tasks using heterogeneous distributed computing systems are studied. Two types of mapping heuristics are considered, immediate mode and batch mode heuristics. Three new heuristics, one for batch mode and two for immediate mode, are introduced as part of this research. Simulation studies are performed to compare these heuristics with some existing ones. In total five immediate mode heuristics and three batch mode heuristics are examined. The immediate mode dynamic heuristics consider, to varying degrees and in different ways, task affinity for different machines and machine ready times. The batch mode dynamic heuristics consider these factors, as well as aging of tasks waiting to execute. The simulation results reveal that the choice of which dynamic mapping heuristic to use in a given heterogeneous environment depends on parameters such as (a) the structure of the heterogeneity among tasks and machines and (b) the arrival rate of the tasks.

A comparison study of static mapping heuristics for a class of meta-tasks on heterogeneous computing systems

Heterogeneous computing (HC) environments are well suited to meet the computational demands of large, diverse groups of tasks (i.e., a meta-task). The problem of mapping (defined as matching and scheduling) these tasks onto the machines of an HC environment has been shown, in general, to be NP-complete, requiring the development of heuristic techniques. Selecting the best heuristic to use in a given environment, however, remains a difficult problem, because comparisons are often clouded by different underlying assumptions in the original studies of each heuristic. Therefore, a collection of eleven heuristics from the literature has been selected, implemented, and analyzed under one set of common assumptions. The eleven heuristics examined are opportunistic load balancing, user-directed assignment, fast greedy, min-min, max-min, greedy, genetic algorithm, simulated annealing, genetic simulated annealing, tabu, and A*. This study provides one even basis for comparison and insights into circumstances where one technique will outperform another. The evaluation procedure is specified, the heuristics are defined, and then selected results are compared.

A dynamic matching and scheduling algorithm for heterogeneous computing systems

A heterogeneous computing system provides a variety of different machines, orchestrated to perform an application whose subtasks have diverse execution requirements. The subtasks must be assigned to machines (matching) and ordered for execution (scheduling) such that the overall application execution time is minimized. A new dynamic mapping (matching and scheduling) heuristic called the hybrid remapper is presented here. The hybrid remapper is based on a centralized policy and improves a statically, obtained initial matching and scheduling by remapping to reduce the overall execution time. The remapping is non-preemptive and the execution of the hybrid remapper can be overlapped with the execution of the subtasks. During application execution, the hybrid remapper uses run-time values for the subtask completion times and machine availability times whenever possible. Therefore, the hybrid remapper bases its decisions on a mixture of run-time and expected values. The potential of the hybrid remapper to improve the performance of initial static mappings is demonstrated using simulation studies.

Integrating trust into grid resource management systems

Grid computing systems that have been the focus of much research in recent years provide a virtual framework for controlled sharing of resources across institutional boundaries. Security is a major concern in any system that enables remote execution. Several techniques can be used for providing security in grid systems including sandboxing, encryption, and other access control and authentication mechanisms. The additional overhead caused by these mechanisms may negate the performance advantages gained by grid computing. Hence, we contend that it is essential for the scheduler to consider the security implications while performing resource allocations. In this paper, we present a trust model for grid systems and show how the model can be used to incorporate security implications into scheduling algorithms. Three scheduling heuristics that can be used in a grid system are modified to incorporate the trust notion and simulations are performed to evaluate the performance.

A taxonomy for describing matching and scheduling heuristics for mixed-machine heterogeneous computing systems

The problem of mapping (defined as matching and scheduling) tasks and communications onto multiple machines and networks in a heterogeneous computing (HC) environment has been shown to be NP-complete, in general, requiring the development of heuristic techniques. Many different types of mapping heuristics have been developed in recent years. However, selecting the best heuristic to use in any given scenario remains a difficult problem. Factors making this selection difficult are discussed. Motivated by these difficulties, a new taxonomy for classifying mapping heuristics for HC environments is proposed (Purdue HC Taxonomy). The taxonomy is defined in three major parts: the models used for applications and communication requests; the models used for target hardware platforms; and the characteristics of mapping heuristics, Each part of the taxonomy is described, with examples given to help clarify the taxonomy. The benefits and uses of this taxonomy are also discussed.

Heterogeneous Distributed Computing

The sections in this article are 1 Examples of HC Application Studies 2 Examples of HC Environments and Tools 3 PVM and HeNCE 4 Taxonomies of Heterogeneous Computing 5 A Conceptual Model of Heterogeneous Computing 6 Task Profiling and Analytical Benchmarking 7 Matching and Scheduling 8 Matching and Scheduling Metatasks 9 Summary and Future Directions 10 Acknowledgment

A localized certificate revocation scheme for mobile ad hoc networks

The issue of certificate revocation in mobile ad hoc networks (MANETs) where there are no on-line access to trusted authorities, is a challenging problem. In wired network environments, when certificates are to be revoked, certificate authorities (CAs) add the information regarding the certificates in question to certificate revocation lists (CRLs) and post the CRLs on accessible repositories or distribute them to relevant entities. In purely ad hoc networks, there are typically no access to centralized repositories or trusted authorities; therefore the conventional method of certificate revocation is not applicable. In this paper, we present a decentralized certificate revocation scheme that allows the nodes within a MANET to revoke the certificates of malicious entities. The scheme is fully contained and it does not rely on inputs from centralized or external entities.

A trust based approach for protecting user data in social networks

Social networks are graphs that represent relations among people, institutions, and their activities. We introduce a novel social access control (SAC) strategy inspired by multi-level security (MLS) [1] for protecting data on social networks. In MLS, the data objects and subjects are classified in hierarchical levels based on security clearance and access controlled accordingly. Instead of clearance levels, we use trust levels to annotate objects and subjects. The trust level of an object is specified by the creator. The trust level of a subject is obtained from a trust modeling process [2, 3]. Reading a data object is controlled using the relative trust values of subjects and objects. We describe one aspect of the SAC model that supports the confidentiality of read-only data objects. We performed simulation studies using traces from the flickr.com social network to evaluate the performance of some key primitives used in the SAC design.