in industries along with our current work towards realizing market-oriented resource allocation of Clouds as realized in Aneka enterprise Cloud technology. Furthermore, we highlight the difference between High Performance Computing (HPC) workload and Internet-based services workload. We also describe a meta

service. Experimental results from a prototype confirm that the system adapts to offered load and resource avail-ability, and can reduce server energy usage by 29 % or more for a typical Web workload. 1.

information from beacons spread throughout the building. Cricket is the result of several design goals, including user privacy, decentralized administration, network heterogeneity, and low cost. Rather than explicitly tracking user location, Cricket helps devices learn where they are and lets them decide whom

The widespread distribution and availability of smallscale sensors, actuators, and embedded processors is transforming the physical world into a computing platform. One such example is a sensor network consisting of a large number of sensor nodes that combine physical sensing capabilities

and monitoring, and hence for planning and adapting application behavior. We present here an information services architecture that addresses performance, security, scalability, and robustness requirements. Our architecture defines simple low-level enquiry and registration protocols that make it easy

We discuss the design of an acquisitional query processor for data collection in sensor networks. Acquisitional issues are those that pertain to where, when, and how often data is physically acquired (sampled) and delivered to query processing operators. By focusing on the locations and costs of acquiring data, we are able to significantly reduce power consumption over traditional passive systems that assume the a priori existence of data. We discuss simple extensions to SQL for controlling data acquisition, and show how acquisitional issues influence query optimization, dissemination, and execution. We evaluate these issues in the context of TinyDB, a distributed query processor for smart sensor devices, and show how acquisitional techniques can provide significant reductions in power consumption on our sensor devices. Categories and Subject Descriptors: H.2.3 [Database Management]: Languages—Query languages; H.2.4 [Database Management]: Systems—Distributed databases; query processing

We consider routing security in wireless sensor networks. Many sensor network routing protocols have been proposed, but none of them have been designed with security as agq1( We propose securitygcur forrouting in sensor networks, show how attacks agacks ad-hoc and peer-to-peer networks can be adapted into powerful attacks agacks sensor networks, introduce two classes of novel attacks agacks sensor networks----sinkholes and HELLO floods, and analyze the security of all the major sensor networkrouting protocols. We describe crippling attacks against all of them and sug@(5 countermeasures anddesig considerations. This is the first such analysis of secure routing in sensor networks.

The World Wide Web has succeeded in large part because its software architecture has been designed to meet the needs of an Internet-scale distributed hypermedia system. The modern Web architecture emphasizes scalability of component interactions, generality of interfaces, independent deployment of components, and intermediary components to reduce interaction latency, enforce security, and encapsulate legacy systems. In this paper, we introduce the Representational State Transfer (REST) architectural style, developed as an abstract model of the Web architecture to guide our redesign and definition of the Hypertext Transfer Protocol and Uniform Resource Identifiers. We describe the software engineering principles guiding REST and the interaction constraints chosen to retain those principles, contrasting them to the constraints of other architectural styles. We then compare the abstract model to the currently deployed Web architecture in order to elicit mismatches between the existing protocols and the applications they are intended to support.

To support the sharing and reuse of formally represented knowledge among AI systems, it is useful to define the common vocabulary in which shared knowledge is represented. A specification of a representational vocabulary for a shared domain of discourse — definitions of classes, relations, functions, and other objects — is called an ontology. This paper describes a mechanism for defining ontologies that are portable over representation systems. Definitions written in a standard format for predicate calculus are translated by a system called Ontolingua into specialized representations, including frame-based systems as well as relational languages. This allows researchers to share and reuse ontologies, while retaining the computational benefits of specialized implementations. We discuss how the translation approach to portability addresses several technical problems. One problem is how to accommodate the stylistic and organizational differences among representations while preserving declarative content. Another is how to translate from a very expressive language into restricted languages, remaining system-independent while preserving the computational efficiency of implemented systems. We describe how these problems are addressed by basing Ontolingua itself on an ontology of domain-independent, representational idioms.

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