Titlebook: Requirements Engineering for Service and Cloud Computing; Muthu Ramachandran,Zaigham Mahmood Book 2017 Springer International Publishing A

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Ana Sofia Zalazar,Luciana Ballejos,Sebastian Rodriguez-based traffic flow model. We show that the proposed approach can solve a dynamic user-optimal route guidance problem based on users’ local outgoing link choice decisions. The numerical studies are implemented by considering two classes of users in the system: informed and non-informed users. The re

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Ana Sofia Zalazar,Luciana Ballejos,Sebastian Rodriguezted in terms of energy consumption, delay, and it is compared with conventional MAC schemes. The result thus obtained using GH-MAC protocol shows that the energy consumption is enormously reduced and thereby the lifetime of the sensor network is enhanced.

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Individual

Gitosree Khan,Sabnam Sengupta,Anirban Sarkarmic properties, it has certain practical limitations. The second solution approach, which we call BIC-B (Bayesian incentive compatible broadcast), overcomes the limitations of the DSIC-B protocol and also has several attractive properties. This chapter is a detailed extension of the results presente

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What We Say We Want and What We Really Need: Experiences on the Barriers to Communicate Information well under way. Finally, the required system architecture cannot be appropriately designed, if we do not know the requirements at a sufficient level. In this chapter we reflect our experiences from participating in a number of large, commercial information system development projects in both public

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Analyzing Requirements Engineering for Cloud Computingally, cloud stakeholders have got neither guidelines nor standards to manage multiple aspects of services in cloud environments. Thus, a literature review was first conducted and five dimensions are discussed (i.e., Contractual, Compliance, Financial, Operational, and Technical) in order to classify

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Classification of Non-functional Requirements of Web Services from Multiperspective Viewuality of Service (OAEQoS) is presented. Due to the extensible nature of PCB-QoS classification, it can be extended to accommodate more number of QoS parameters. This QoS classification is based on the idea of partitioning the generic QoS parameters according to multi-user’s perspective. An Average