A Resource-aware Service Discovery Architecture for Ad-hoc Mobile Cloud

Abstract

The synergy between Mobile Cloud Computing and the proliferation of smart devices is increasingly expanding the interaction space for mobile web services delivery. More so, with the rising prominence of the IoT paradigm, which seeks to drive a smarter and unlimited interconnected interaction between diverse devices, the need for opportunistic and inexpensive service provisioning platforms becomes more imperative. Such platforms stand to potentially contribute toward realizing the Ad-hoc Mobile Cloud model which advocates the idea of mobile web services (MWS): enabling mobile and other smart devices to function as service providers in addition to their conventional role as service requesters. However, mobile, and smart devices are inherently characterized by limitations in resources such as battery power, memory, and storage capacities. Consequently, executing service discovery operation on the local device can introduce a huge resource burden. Therefore, to achieve service discovery in such a decentralized mobile device-enabled e-services provisioning platform without compromising the devices' resources requires an architecture designed to support capabilities for proactive resource management. In this paper, we propose an architecture that supports service discovery in Ad-hoc Mobile Cloud (AMC) through a mechanism driven by resource-awareness.

Service Discovery in Mobile Ad-Hoc Environments: A Solution Space Analysis

“…Due to the dynamic nature of AMEs, the relevance of discovered services is highly context-dependent [2]. This dependence coupled with the diversity of the characteristics of the constituents of AMEs and their requirements, the need to expand the conventional scope of what constitutes context to include device characteristics have been highly advocated [11], [29]. This advocacy seems to be gaining significant research attention as half of the reviewed papers proposed techniques that employed the device context approach toward service personalization.…”

“…Furthermore, with the emergent of IoTs, where a smart device either be a service consumer or itself a service, then the concept of "user" needs to be re-modeled in the scope of context. This will require new context models as advocated in [11]. Adaptation/Ranking Technique: As the volume of web services continue to grow and devices become smarter and more capable, the demand to render services in a smarter and more user adapted manner will grow proportionately.…”

“…Addressing these aforementioned challenges has motivated the advent of various Ad-hoc Mobile Cloud computing paradigms. This paradigm is a complementary approach to MCC, which consists, instead, in enabling either direct service provisioning between mobile devices or indirect service provisioning a community mobile devices in collaboration with a Cloudlet [10], [11]. These devices exploit self-organizing networks to support direct communication with each other [12].…”

An Energy-Efficient priority Scheduling Technique for Disaster Response Cellular Networks

“…In order to overcome this problem, the D2D communication was considered where UE collects RF energy from the base station. In [16], the author discussed a resource aware scheduling strategy for mobile networks with cloud platform.…”

Mobile Web Service Discovery: A Cloudlet Mediated Framework

“…Web services have continued to soar in popularity in the last decade, terms of the scale of their adoption and scope of application [1], [2]. As a result, the Web services concept now fundamentally defines the core of global business models because of its associated benefits of flexibility and cost-effectiveness, among other advantages.…”