Realization of industry-scale, goal-driven, autonomous systems with AI planning technology faces several challenges: flexibly specifying planning goal states in varying situations, synthesizing plans in large state spaces, re-planning in dynamic situations, and facilitating humans to supervise, give feedback and intervene. In this paper, we present Intent-driven Strategic Tactical Planning (ISTP) to address these challenges. We demonstrate its efficacy through its application for radio base station inspection across several locations using drones. The inspection task involves capturing images, thermal images or signal measurements - called knowledge-objects - of various components of the base stations for downstream processing. In the ISTP approach, an operator indicates her goals by flying the drone to different components of interest. These goals are generalized to capture the intent of the operator, which are then instantiated in new situations to generate goals dynamically. Towards planning and re-planning in large state spaces to achieve these goals efficiently, we extend the Strategic-Tactical Planning paradigm. All the components of ISTP are integrated in an intuitive UI and demonstrated through a real life use-case built on the UNITY simulator platform.

Supporting fast access to large RDF stores has been one of key challenges for enabling use of the Semantic Web in real-life applications, more so in sensor-based systems where large amounts of historic data needs to be stored. We propose a semantics-based temporal view mechanism that enables faster access to time-varying data by caching into memory only the required subset of RDF triples. We describe our experience of implementing such a framework in the context of a wide area network monitoring system. Our preliminary results show that our solution significantly improves client access time and scales well for moderate data sets.

Application checkpoint and restart has been a widely studied problem over the last several decades. Despite immense volume of theory and several research project level implementations, there is very little by way of working solutions for the case of parallel distributed applications (such as MPI programs on a cluster). We describe our experiences in enhancing a job scheduler to leverage mechanisms of a virtual machine environment to support checkpoint-restart. We also describe the basic coordinated checkpoint-restart framework that we implemented on which this solution is based.

Dependency tracking between communicating tasks is an important concept in backward error recovery for parallel applications. One can extend the traditional dependence tracking model for message passing systems to track dependencies between shared memory and task private states for shared memory applications. The objective of this paper is to analyze the issues generated by locks and barriers in parallel applications so that we can checkpoint tasks at any time (even when holding or waiting for locks and barriers). In particular we attempt to extend earlier dependency tracking mechanisms to locks and barriers. We address both coordinated and uncoordinated checkpointing schemes.

Cluster federations are attractive for executing applications like large scale code coupling. However faults may appear frequently in such architectures. Thus, checkpointing long-running applications is desirable to avoid to restart them from the beginning in the event of a node failure. To take into account the constraints of a cluster federation architecture, an hybrid checkpointing protocol is proposed. It uses global coordinated checkpointing inside clusters but only quasi-synchronous checkpointing techniques between clusters. The proposed protocol has been evaluated by simulation and fits well for applications that can be divided into modules with lots of communications within modules but few between them.

Summary form only given. Code coupling applications can be divided into communicating modules, that may be executed on different clusters in a cluster federation. As a cluster federation comprises of a large number of nodes, there is a high probability of a node failure. We propose a hierarchical checkpointing protocol that combines a synchronized checkpointing technique inside clusters and a communication-induced technique between clusters. This protocol fits to the characteristics of a cluster federation (large number of nodes, high latency and low bandwidth networking technologies between clusters). A preliminary performance evaluation performed using a discrete event simulator shows that the protocol is suitable for code coupling applications.

This paper describes issues in the design and implementation of checkpointing and recovery modules for the Kerrighed DSM cluster system. Our design is for a DSM supporting the sequential consistency model. The mechanisms are general enough to be used in a number of different checkpointing and recovery protocols. It is designed to support common optimizations for performance suggested in literature, while staying light-weight during fault free execution. We also present preliminary performance results of the current implementation.

Abstract Checkpoint and rollback recovery is a well‐known technique for providing fault tolerance to long‐running distributed applications. Performance of a checkpoint and recovery protocol depends on the characteristics of the application and the system on which it runs. However, given an application and system environment, there is no easy way to identify which checkpoint and recovery protocol will be most suitable for it. Conventional approaches require implementing the application with all the protocols under consideration, running them on the desired system, and comparing their performances. This process can be very tedious and time consuming. This paper first presents the design and implementation of a simulation environment, distributed process simulation or dPSIM, which enables easy implementation and evaluation of checkpoint and recovery protocols. The tool enables the protocols to be simulated under a wide variety of application, system, and network characteristics. The paper then presents performance evaluation of five checkpoint and recovery protocols. These protocols are implemented and executed in dPSIM under different simulated application, system, and network characteristics. Copyright © 2003 John Wiley & Sons, Ltd.

With increased data rates, the packet transmission time of a LAN could approach or even become less than the medium propagation delay. The performance of many LAN schemes degrades rapidly under these conditions. Generally, the overhead associated with the medium access protocol increases with the increase in propagation time relative to packet transmission time. In token ring networks this overhead depends on the round trip propagation delay of the channel. Several schemes, such as multiple rings (with multiple channels) and multiple access points (with multiple tokens) are proposed to decrease this overhead. In these schemes analytical and simulation results have shown improved performance. In the present paper we propose a distributed multiconnected loop topology with multiple tokens. We also present analytical results showing the packet delay performance. Finally we compare the performance of distributed multiconnected loops with multiple ring topology in terms of media access control, token coalescence and delay.

In this paper, we present a scheme for efficient embedding of torus of any dimension on a star graph. The dilation of the embedding is four. The expansion is small. Congestion depends upon the routing scheme used. With one routing scheme, the congestion is bound by a small constant (/spl ap/2) with an increase in expansion cost. For a second routing scheme, the congestion is O(n), for an n-star, with bounded expansion.

In this paper we present a scheme for congestion-free embedding of full binary trees on a star graph. The height of the tree that can be embedded with this scheme in an n-star is (n+1)[log/sub 2/n]-2/sup [log2n]+1/+1. The dilation of the embedding is two. This is an improvement by a factor of two over an earlier result.