Imran Rao

A probabilistic and adaptive scheduling algorithm using system-generated predictions for inter-grid resource sharing

Abstract Rapid advancement and more readily availability of Grid technologies have encouraged many businesses and researchers to establish Virtual Organizations (VO) and make use of their available desktop resources to solve computing intensive problems. These VOs, however, work as disjointed and independent communities with no resource sharing between them. We, in previous work, have proposed a fully decentralized and reconfigurable Inter-Grid framework for resource sharing among such distributed and autonomous Grid systems (Rao et al. in ICCSA, [2006]). The specific problem that underlies in such a collaborating Grids system is scheduling of resources as there is very little knowledge about availability of the resources due to the distributed and autonomous nature of the underlying Grid entities. In this paper, we propose a probabilistic and adaptive scheduling algorithm using system-generated predictions for Inter-Grid resource sharing keeping collaborating Grid systems autonomous and independent. We first use system-generated job runtime estimates without actually submitting jobs to the target Grid system. Then this job execution estimate is used to predict the job scheduling feasibility on the target system. Furthermore, our proposed algorithm adapted itself to the actual resource behavior and performance. Simulation results are presented to discuss the correctness and accuracy of our proposed algorithm.

Impacts of Asynchrony on Epidemic-Style Aggregation Protocols

The large scale and dynamic nature of a distributed system makes it difficult to collect the attributes of the individual nodes in the network. In these systems, often an aggregate (e.g. AVG, COUNT, MIN, MAX, SUM etc) of these attributes is adequate. Epidemic-style protocols are one of the popular approaches to estimate aggregates in such systems. In existing epidemic-style aggregation protocols the accuracy of the estimated aggregate at local nodes heavily depends upon synchronization of aggregation rounds. To enforce synchronization in these protocols, length of aggregation round should be long enough so that all the nodes in the system complete their aggregation information exchange. In this paper, we study the impacts of asynchrony in epidemic-style aggregation protocols. We present a simple asynchronous technique to estimate system aggregates in a distributed system. Based upon this technique, we analyze two popular existing epidemic-style aggregation protocols, Push-Pull and Push-Sum. Through detailed simulations, we evaluate accuracy and cost of asynchronous version of these protocols. We found that to obtain an estimate of the true system aggregate, aggregation protocols do not need to be synchronized and hence an efficient estimate can be obtained in lesser time.

An Adaptive and Efficient Design and Implementation for Meteorology Data Grid Using Grid Technology

Grid technologies not only provide the infrastructure to collaborate among virtual organizations to share heterogeneous resources but also provide a service oriented paradigm for business and social software development. In this paper, we present an agent based efficient and adaptive design for our meteorological data portal system, called meteo-data grid and its implementation using grid technology. Our adaptive agent based approach analyzes the workload and then invoke or revoke agents using factory design pattern to process the data files of gigabyte scale. We also investigated the suitability of grid technologies for a portal based data management system in comparison with currently available Web technologies, namely Web services and Java servlets and evaluated their performance in terms of response time to retrieve varying amount of data from database and serve to GridSphere portlet. Our experiments results show that to serve large scale of data, grid services are much faster as compared to Web services and Java servlets

Gossip-based asynchronous and robust aggregation protocol — A pessimistic approach

Gossip-based protocols are one of the popular approaches to estimate aggregates in large scale distributed systems. In this paper, we propose a gossip-based asynchronous and robust protocol to compute aggregates. In our protocol, each node employs the proposed pessimistic approach to exchange its local estimate with one of its neighbors and also uses the proposed recovery scheme which conserves the system mass in the presence of asynchrony and churn. The simulation results presented in this paper show that our protocol yields accurate aggregates in comparatively lesser time.

A gossip-based asynchronous aggregation protocol for P2P systems

Gossip-based protocols are a popular approach to estimate aggregates in P2P systems. For gossip-based aggregation protocols, the accuracy of the estimated aggregate heavily depends upon conservation of the system mass. In this paper, we present a gossip-based asynchronous aggregation protocol. Our protocol conserves the system mass under asynchronous settings and churn. Simulation results show that our proposed protocol converges to the correct system aggregate even in the presence of very dynamic and adverse network delays and under churn.

A Membership Scheme for Gossip based Reliable Data Dissemination in Ad-hoc WSNs

Wireless Sensor Networks (WSNs) generate bulk amount of live data and events sensed through dispersedly deployed tiny sensors. The data needed to be disseminate to the sink little consumption of network resources. Gossiping is an intrinsic choice of researcher for disseminating bulk data in unstructured ad-hoc wireless networks. An important issue in gossip-based dissemination protocols is to keep routing table up to date. In this paper we propose a novel membership algorithm for gossip-based data dissemination in ad-hoc wireless sensor networks. The goal of our proposed protocol is to keep the routing table size H low, and at the same time, ensure network diameter is small. We study the behavior of our proposed membership protocol through simulations. Through extensive experimental evaluation and comparison, we demonstrate that our protocol achieves significant improvements in network reachibility and network connectivity.

An unstructured peer-to-peer approach to aggregate node selection

In distributed and high performance applications it it is necessary to discover the aggregate resource capabilities of the collaborating peers. Another requirement of these applications is to locate the resources meeting the given aggregate search criteria. In this paper we present an unstructured peer-to-peer approach to aggregate node selection for resource management. Our objective is to efficiently calculate the aggregate value and search the aggregate node whose attribute matches or falls in the proximity of this value. Our contribution also includes the inclusion of an explicit network for aggregate query routing. We evaluated our protocol for accuracy, efficiency and communication cost through detailed simulations.

Adaptive expression based routing protocol for P2P systems

There is an emerging trend of using P2P systems for computational and data intensive tasks, such as online collaborations, distributed database applications and message passing interface (MPI) algorithms. For better resource utilization in these and similar applications, it is necessary to discover the resource capabilities of the collaborating peers. Another requirement of these applications is to locate the optimal resource based on a search criteria, e.g., to seek a resource with earliest execution time. We define this kind of routing as expression based routing. However, in the absence of the centralized controlling node, tracking the capabilities of the participating peers is very difficult. Moreover peers join and leave the system dynamically and, thus, makes the discovery of a desired resource even more complex. In this paper we investigate a novel algorithm for expression based routing in a P2P system. It evaluates peer u such that lu (the value of u) is minimum where e.g. lu is load of the peer u. Our contribution includes a detailed algorithm to search for the least loaded peer in the system. We analyze the accuracy and cost of our proposed algorithm through detailed simulations.

A proxy-based uncoordinated checkpointing scheme with pessimistic message logging for mobile grid systems

Due to mobility, energy limitations, and unreliable wireless channels, applications running on mobile devices suffer from faults such as temporary disconnection and data loss. We, therefore, need a fault tolerance mechanism to guarantee their smooth working and performance. In this paper, we present a novel proxy-based uncoordinated checkpointing scheme with pessimistic message logging for efficient fault recovery in mobile Grid system. Simulation results show that this scheme is reliable, efficient and, at the sametime, consumes less network traffic.

On Problem for Aggregate Node Selection for Unstructured Overlay Networks

With the success of the peer-to-peer systems, there is an emerging trend to develop an aggregation service that can provide global information about these distributed and decentralized overlays. Existing aggregation protocols have focused on providing an efficient and cost effective solution to compute aggregates. In this paper, we are interested to search the node based on an aggregate query over rapidly changing data e.g., to seek a node with minimum/maximum workload in the network. Solution to such queries can benefit number of applications such as, node-ranking, reputation building, resource scheduling, etc. Here we propose a novel protocol to solve such queries. Our proposed protocol is reactive and pull-based in nature. It intrinsically builds and manages a routing table which routes aggregate query to the desired node in the system. We evaluated our protocol for accuracy, efficiency and communication cost through detailed simulations. We also discuss effects of an explicit routing table management scheme and show that this explicit scheme causes our protocol to work better in presence of churn and node failures.