Context based service discovery algorithm for ad hoc mobile cloud

Egbe, Dominic Afuro; Akingbesote, Alaba Olu; Adigun, Matthew O.; Mutanga, Murimo Bethel

doi:10.1109/iccsii.2016.7462411

Cited by 6 publications

(4 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Without thinking carefully about some circumstances, such as functional, non-functional, and budgetary limitations, it is not probable to discover the numerous cloud providers ( Kapil et al, 2020 ). Therefore, efficient service discovery in the cloud is a significant challenge and an essential part of any distributed system ( Srirama, Paniagua & Liivi, 2013 ; Navimipour et al, 2014 ; Egbe et al, 2016 ). However, cloud computing managers can automatically or semi-automatically detect services or service information ( Afify et al, 2014 ; Zhang et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

A new SLA-aware method for discovering the cloud services using an improved nature-inspired optimization algorithm

Heidari

Navimipour

2021

PeerJ Computer Science

View full text Add to dashboard Cite

Cloud computing is one of the most important computing patterns that use a pay-as-you-go manner to process data and execute applications. Therefore, numerous enterprises are migrating their applications to cloud environments. Not only do intensive applications deal with enormous quantities of data, but they also demonstrate compute-intensive properties very frequently. The dynamicity, coupled with the ambiguity between marketed resources and resource requirement queries from users, remains important issues that hamper efficient discovery in a cloud environment. Cloud service discovery becomes a complex problem because of the increase in network size and complexity. Complexity and network size keep increasing dynamically, making it a complex NP-hard problem that requires effective service discovery approaches. One of the most famous cloud service discovery methods is the Ant Colony Optimization (ACO) algorithm; however, it suffers from a load balancing problem among the discovered nodes. If the workload balance is inefficient, it limits the use of resources. This paper solved this problem by applying an Inverted Ant Colony Optimization (IACO) algorithm for load-aware service discovery in cloud computing. The IACO considers the pheromones’ repulsion instead of attraction. We design a model for service discovery in the cloud environment to overcome the traditional shortcomings. Numerical results demonstrate that the proposed mechanism can obtain an efficient service discovery method. The algorithm is simulated using a CloudSim simulator, and the result shows better performance. Reducing energy consumption, mitigate response time, and better Service Level Agreement (SLA) violation in the cloud environments are the advantages of the proposed method.

show abstract

Section: Introductionmentioning

confidence: 99%

A new SLA-aware method for discovering the cloud services using an improved nature-inspired optimization algorithm

Heidari

Navimipour

2021

PeerJ Computer Science

View full text Add to dashboard Cite

show abstract

“…To address this challenge, the Ad-hoc Mobile Cloud (AMC) paradigm serves to complement MCC by "enabling a platform for inexpensive and collaborative" [20] mobile service provisioning where services are co-hosted and discovered among peer devices when the main cloud is inaccessible [21]. However, the unique nature of the AMC and the envisaged role of mobile peers also present unique service discovery challenges that cannot be suitably addressed by conventional MCC solution approaches.…”

Section: Introductionmentioning

confidence: 99%

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

Egbe¹

2020

IJETER

Self Cite

View full text Add to dashboard Cite

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.

show abstract

“…Therefore AMC is a network of mobile devices that act as Cloud providers by enabling each device to expose its resources to others within the network [13]. That is, in the AMC scenario, a mobile node can host web services that are discovered and invoked by other mobile nodes within the ad-hoc network [14]- [16]. In realizing these emerging mobile computing paradigms, significant research is ongoing toward optimizing service discovery techniques to suit the particular characteristics of these environments.…”

Section: Introductionmentioning

confidence: 99%

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

Mutanga¹

2020

IJETER

View full text Add to dashboard Cite

The rapid and pervasive growth of Cloud computing and SOA has given rise to a lot of other remarkable offshoots. One interesting feature of this trend has been the emergence of the Ad-hoc Mobile Cloud (AMC) paradigm. Ad-hoc Mobile Cloud allows users to collaborate and share web services in a platform that enables mobile devices to play the role of service providers. This peculiar functional architecture that relies on resource-limited devices to host and perform discovery operations introduces another dimension to the service discovery challenge in conventional mobile environments. The conventional Cloud and Mobile Cloud environments leverage on the limitless cloud storage and computing power, therefore, techniques designed for such environments are generally resource-unaware. Consequently, the traditional service discovery mechanisms designed for Cloud computing cannot be adopted into AMC. In this review, we present an analysis of how service discovery solutions in Ad-hoc Mobile Cloud have adapted to meet the unique challenges of this resource-constrained environment. We classified, at a generic level, the solution space of the current service discovery techniques in Ad-hoc mobile cloud, and the identify opportunities for advancing research in the domain.

show abstract

Context based service discovery algorithm for ad hoc mobile cloud

Cited by 6 publications

References 15 publications

A new SLA-aware method for discovering the cloud services using an improved nature-inspired optimization algorithm

A new SLA-aware method for discovering the cloud services using an improved nature-inspired optimization algorithm

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

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

Contact Info

Product

Resources

About