Reliable Fault Tolerance System for Service Composition in Mobile Ad Hoc Network

A Due to the rapid development of smart processing mobile devices, Mobile applications are exploring the use of web services in MANETs to satisfy the user needs. Complex user needs are satisfied by the service composition where a complex service is created by combining one or more atomic services. Service composition has a significant challenge in MANETs due to its limited bandwidth, constrained energy sources, dynamic node movement and often suffers from node failures. These constraints increase the failure rate of service composition. To overcome these, we propose Reliable Fault Tolerant System for Service Composition in MANETs (RFTSC) which makes use of the checkpointing technique for service composition in MANETs. We propose fault policies for each fault in service composition when the faults occur. Failure of services in the service composition process is recovered locally by making use of Checkpointing system and by using discovered services which satisfies the QoS constraints. A Multi-Service Tree (MST) is proposed to recover failed services with O(1) time complexity. Simulation result shows that the proposed approach is efficient when compared to existing approaches

Execution/Simulation of Context/Constraint-aware Composite Services using GIPSY

For fulfilling a complex requirement comprising of several sub-tasks, a composition of simple web services, each of which is dedicated to performing a specific sub-task involved, proves to be a more competent solution in comparison to an equivalent atomic web service. Owing to advantages such as re-usability of components, broader options for composition requesters and liberty to specialize for component providers, for over two decades now, composite services have been extensively researched to the point of being perfected in many aspects. Yet, most of the studies undertaken in this field fail to acknowledge that every web service has a limited context in which it can successfully perform its tasks, the boundaries of which are defined by the internal constraints placed on the service by its providers. When used as part of a composition, the restricted context-spaces of all such component services together define the contextual boundaries of the composite service as a unit, which makes internal constraints an influential factor for composite service functionality. However, due to the limited exposure received by them, no systems have yet been proposed to cater to the specific verification of internal constraints imposed on components of a composite service. In an attempt to address this gap in service composition research, in this thesis, we propose a multi-faceted solution capable of not only automatically constructing context-aware composite web services with their internal constraints positioned for optimum resource-utilization but also of validating the generated compositions using the General Intensional Programming SYstem (GIPSY) as a time- and cost-efficient simulation/execution environment

DATESSO: Self-Adapting Service Composition with Debt-Aware Two Levels Constraint Reasoning

The rapidly changing workload of service-based systems can easily cause under-/over-utilization on the component services, which can consequently affect the overall Quality of Service (QoS), such as latency. Self-adaptive services composition rectifies this problem, but poses several challenges: (i) the effectiveness of adaptation can deteriorate due to over-optimistic assumptions on the latency and utilization constraints, at both local and global levels; and (ii) the benefits brought by each composition plan is often short term and is not often designed for long-term benefits -- a natural prerequisite for sustaining the system. To tackle these issues, we propose a two levels constraint reasoning framework for sustainable self-adaptive services composition, called DATESSO. In particular, DATESSO consists of a re ned formulation that differentiates the "strictness" for latency/utilization constraints in two levels. To strive for long-term benefits, DATESSO leverages the concept of technical debt and time-series prediction to model the utility contribution of the component services in the composition. The approach embeds a debt-aware two level constraint reasoning algorithm in DATESSO to improve the efficiency, effectiveness and sustainability of self-adaptive service composition. We evaluate DATESSO on a service-based system with real-world WS-DREAM dataset and comparing it with other state-of-the-art approaches. The results demonstrate the superiority of DATESSO over the others on the utilization, latency and running time whilst likely to be more sustainable.Comment: Accepted to the SEAMS '20. Please use the following citation: Satish Kumar, Tao Chen, Rami Bahsoon, and Rajkumar Buyya. DATESSO: Self-Adapting Service Composition with Debt-Aware Two Levels Constraint Reasoning. In IEEE/ACM 15th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, Oct 7-8, 2020, Seoul, Kore

A QoS aware services mashup model for cloud computing applications

Purpose: With the popularity of cloud computing, cloud services have become to be application programming platform where users can create new applications mashup(composing) the functionality offered byothers.By composing of distributed, cloud services dynamicallyto provide more complex tasks, services mashup provides an attractive way for building large-scale Internet applications.One of the challenging issues of cloud services mashup is how to find service paths to route the service instances provider through whilemeeting the applications’ resource requirements so that the QoS constraints are satisfied. However, QoS aware service routing problem istypically NP-hard.The purpose of this paper is to propose a QoS Aware Services Mashup(QASM) model to solve this problem more effectively. Design/methodology/approach: In this paper, we focus on the QoS aware services selection problem in cloud services mashup, for example, given the user service composition requirements and their QoS constraint descriptions, how to select the required serviceinstances and route the data flows through these instances so that the QoS requirements are satisfied. We design a heuristic algorithm to find service paths to route the data flows through whilemeeting the applications’ resource requirements and specific QoS constraints. Findings: This study propose a QoS Aware Services Mashup(QASM) model to solve this problem more effectively. Simulations show that QASM can achieve desired QoS assurances as well as load balancing in cloud services environment. Originality/value: This paper present a QASM model for providing high performance distributed applications in the cloud computingPeer Reviewe