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Parallel and distributed systems may operate in an environment that undergoes unpredictable changes causing certain system performance features to degrade. Such systems need robustness to guarantee limited degradation despite fluctuations in the behavior of its component parts or environment. This research investigates the robustness of an allocation of resources to tasks in parallel and distributed systems. The main contributions of this paper are 1) a mathematical description of a metric for the robustness of a resource allocation with respect to desired system performance features against multiple perturbations in multiple system and environmental conditions, and 2) a procedure for deriving a robustness metric for an arbitrary system. For illustration, this procedure is employed to derive robustness metrics for three example distributed systems. Such a metric can help researchers evaluate a given resource allocation for robustness against uncertainties in specified perturbation parameters.

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In many distributed computing environments, collections of applications need to be processed using a set of heterogeneous computing (HC) resources to maximize some performance goal. An important research problem in these environments is how to assign resources to applications (matching) and order the execution of the applications (scheduling) so as to maximize some performance criterion without violating any constraints. This process of matching and scheduling is called mapping.1Howard Jay Siegel holds a joint appointment in the Computer Science Department as well. 2Albert I. Reuther is currently with MIT Lincoln Laboratory, Lexington, MA. CHARACTERIZING RESOURCE ALLOCATION HEURISTICSTo make meaningful comparisons among mapping heuristics, a system designer needs to understand the assumptions made by the heuristics for (1) the model used for the application and communication tasks, (2) the model used for system platforms, and (3) the attributes of the mapping heuristics. This chapter presents a three-part classification scheme (3PCS) for HC systems. The 3PCS is useful for researchers who want to (a) understand a mapper given in the literature, (b) describe their design of a mapper more thoroughly by using a common standard, and (c) select a mapper to match a given real-world environment.

Agriculture is considered as the main driving force in Pakistan’s economy employing 45% of the country’s labor force and generating 20% of national GDP Agriculture sector of Pakistan is facing numerous challenges including non-adoption of agricultural technology at the farm level, due to farmers’ lack of access to the latest information. In this context, the current study focusses on the use of the mobile phone in accessing agricultural information among the farmers of the of district Muzaffargarh,Punjab, Pakistan. A multistage sampling technique was used to collect data from the two tehsils (cities/sub-districts) of Muzaffargarh formulating a total sample of 180 farmers. SPSS computer-based Software was used for analyzing the data. Results revealed that 91.2% of the farmers indicated mobile phone ownership. It was further reported that 87.20 % of the farmers used private sectors advisory staff to obtain agriculture information. Market information was ranked as the highest accessed information among the rest of farm-related use. Easy access to updated information and connectivity with stakeholders were reported as the highest perceived benefits of mobile phone use (4.63 & 4.72 mean). Findings reported that farmers’ limited aptitude of Mobile phone usage and lack of awareness of information sources as major constraints in farm-related use of the Mobile phone. On the basis of findings, the current study provided recommendations and policy implications for utilizing the true potential of these ICT-enabled solutions in agriculture.

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