Context storage using NoSQL

With the ubiquity and pervasiveness of mobile computing, together with the increasing number of social networks, end-users have learned to live and share all kinds of information about themselves. As an example, Facebook reports that it has currently 500 million active users, 200 million of which access its services on mobile systems; moreover, users that access Facebook through mobile applications are twice as active as non-mobile users, and it is used by 200 mobile operators in 60 countries [1]. More specific mobile platforms such as Foursquare, which unlike Facebook only collects location information, reports 6.5 million users worldwide, and also has a mobile presence (both with a web application and iPhone / Android applications) [2]. Context- aware architectures intend to explore this increasing number of context information sources and provide richer, targeted services to end-users, while also taking into account arising privacy issues. While multiple context management platform architectures have been devised [3], this paper focuses primarily on Context- Broker-based architectures, such as the ones proposed in the projects Mobilife [4] and C-Cast [5]. More specifically, it focuses on the context management platform XCoA [6]. This platform uses XMPP for its main communication protocol, and publishes context information in a Context-Broker. This context information is provided by Context-Agents, such as mobile terminals, sensor networks and social networks. Due to the nature of the XMPP protocol, the context information is provided in XML form. This paper proposes the usage of a NoSQL storage system for the purpose of context information storage and retrieval in an XMPP broker-based context platform such as XCoA, together with a full-text searching engine. Through a comparison made through prototypes, the paper clearly demonstrates the advantages of NoSQL storage systems applied to the area of Context Management

Computation Offloading Decision in Mobile Cloud Computing: Enhance Battery Life of Mobile Device

Functionality on mobile device is ever richer in daily life. Mobile devices have limited resources like battery life, storage and processor, etc. Nowadays, Mobile Cloud Computing (MCC) bridges the gap between the limited capabilities of mobile devices and the increasing user demand of mobile applications by offloading the computational workloads from local devices to the remote cloud. Deciding to offload some computing tasks or not is a way to solve the limitations of battery life and computing capability of mobile devices. Application offloading is energy efficient only under various conditions for determining where/which code should be executed. This paper presents a Computational Offloading Decision Algorithm (CODA) , to save the battery life of mobile devices, taking into account the CPU load, state of charge, network bandwidth and transmission data size. The system can take decision which method should be offloaded or not based on different context of the mobile device to obtain minimum processing cost. Numerical study is carried out to evaluate the performance of system. Experimental result will demonstrate that the proposed algorithm can significantly reduce energy consumption of mobile device as well as execution time of application

Design and implementation of a multi-agent opportunistic grid computing platform

Opportunistic Grid Computing involves joining idle computing resources in enterprises into a converged high performance commodity infrastructure. The research described in this dissertation investigates the viability of public resource computing in offering a plethora of possibilities through seamless access to shared compute and storage resources. The research proposes and conceptualizes the Multi-Agent Opportunistic Grid (MAOG) solution in an Information and Communication Technologies for Development (ICT4D) initiative to address some limitations prevalent in traditional distributed system implementations. Proof-of-concept software components based on JADE (Java Agent Development Framework) validated Multi-Agent Systems (MAS) as an important tool for provisioning of Opportunistic Grid Computing platforms. Exploration of agent technologies within the research context identified two key components which improve access to extended computer capabilities. The first component is a Mobile Agent (MA) compute component in which a group of agents interact to pool shared processor cycles. The compute component integrates dynamic resource identification and allocation strategies by incorporating the Contract Net Protocol (CNP) and rule based reasoning concepts. The second service is a MAS based storage component realized through disk mirroring and Google file-system’s chunking with atomic append storage techniques. This research provides a candidate Opportunistic Grid Computing platform design and implementation through the use of MAS. Experiments conducted validated the design and implementation of the compute and storage services. From results, support for processing user applications; resource identification and allocation; and rule based reasoning validated the MA compute component. A MAS based file-system that implements chunking optimizations was considered to be optimum based on evaluations. The findings from the undertaken experiments also validated the functional adequacy of the implementation, and show the suitability of MAS for provisioning of robust, autonomous, and intelligent platforms. The context of this research, ICT4D, provides a solution to optimizing and increasing the utilization of computing resources that are usually idle in these contexts

TAME: an Efficient Task Allocation Algorithm for Integrated Mobile Gaming

We consider an integrated mobile gaming platform, in which the mobile device (e.g., smartphone) of a player can offload some game tasks toward a server as well as some neighboring mobile devices. The advantages of such a platform are manyfold: it can lead to an improved game experience, to a better use of energy resources, and, while offloading tasks to other mobile users, to the exploitation of the unused computing and storage resources of the mobile equipments, thus reducing the bandwidth and computing costs of the overall system. In this context, we formulate the problem of offloading the game computational tasks as an optimization problem that minimizes the maximum energy consumption across a set of mobile devices, under the constraints of a maximum response time and a limited availability of computation, communication and storage resources. In light of the problem complexity, we then propose a heuristic, called TAME, which is shown to closely approximate the optimal solution in all scenarios we considered. TAME also outperforms state-of-the-art algorithms under both synthetic and real scenarios, which have been devised based on a realistic and detailed energy consumption model for computation and communication resources. Our results, although tailored to mobile gaming, could be extended to other applications where it may be beneficial to offload computational and storage tasks through device-to-device communications, as enabled by Wi-Fi, Bluetooth, or the upcoming 5G technology

Mobile Cloud Computing Based Technologies for Enhancing E-learning Content Delivery and Sharing in Higher Learning Institutions in Tanzania using Learner-Centered Approach

Electronic learning (E-learning) in Higher Learning Institutions (HLIs) offers a cost-effective teaching and learning that support social interactivity, flexibility, context sensitivity, and active participation of learners in learning activities. The objective of this study was to investigate the challenges facing the traditional E-learning tools and leverage the advanced capacity of Mobile Cloud Computing (MCC) to enhance E-learning service delivery and sharing of learning resources focusing in learner-centered approach. Also, the evolvement of mobile computing devices such as smartphones, Personal Digital Assistance (PDA), and laptops owned by learners bring prospects in overcoming the inherent challenges facing HLIs in developing countries such as shortage of computer laboratories and network resources.Consequently, this study proposes MCC-based E-learning content delivery and sharing to augment higher learning institutions with limited resource setting in developing countries. The main benefits of MCC-based E-learning include, first, augment traditional LMS by provisioning abundant processing capacity and storage in the cloud that guarantee unlimited learning materials available for learners and instructors; Second, improves performance in local Learning Management System (LMS) servers by outsourcing execution and storage into the cloud especially when resource-intensive E-learning contents such as games, Virtual Reality (VR), and video streaming are used for learning; third, supports multi-platforms to execute the workload of various E-learning applications in the cloud which is potential for E-learning resource sharing; and fourth, guarantee cost-effective E-learning content delivery and sharing. Keywords: Mobile cloud computing, E-learning, content delivery, Learner-centered learning DOI: 10.7176/JIEA/13-2-03 Publication date:March 31st 202

Cloud Services Brokerage for Mobile Ubiquitous Computing

Recently, companies are adopting Mobile Cloud Computing (MCC) to efficiently deliver enterprise services to users (or consumers) on their personalized devices. MCC is the facilitation of mobile devices (e.g., smartphones, tablets, notebooks, and smart watches) to access virtualized services such as software applications, servers, storage, and network services over the Internet. With the advancement and diversity of the mobile landscape, there has been a growing trend in consumer attitude where a single user owns multiple mobile devices. This paradigm of supporting a single user or consumer to access multiple services from n-devices is referred to as the Ubiquitous Cloud Computing (UCC) or the Personal Cloud Computing. In the UCC era, consumers expect to have application and data consistency across their multiple devices and in real time. However, this expectation can be hindered by the intermittent loss of connectivity in wireless networks, user mobility, and peak load demands. Hence, this dissertation presents an architectural framework called, Cloud Services Brokerage for Mobile Ubiquitous Cloud Computing (CSB-UCC), which ensures soft real-time and reliable services consumption on multiple devices of users. The CSB-UCC acts as an application middleware broker that connects the n-devices of users to the multi-cloud services. The designed system determines the multi-cloud services based on the user's subscriptions and the n-devices are determined through device registration on the broker. The preliminary evaluations of the designed system shows that the following are achieved: 1) high scalability through the adoption of a distributed architecture of the brokerage service, 2) providing soft real-time application synchronization for consistent user experience through an enhanced mobile-to-cloud proximity-based access technique, 3) reliable error recovery from system failure through transactional services re-assignment to active nodes, and 4) transparent audit trail through access-level and context-centric provenance

Design and implementation of a multi-agent opportunistic grid computing platform

Opportunistic Grid Computing involves joining idle computing resources in enterprises into a converged high performance commodity infrastructure. The research described in this dissertation investigates the viability of public resource computing in offering a plethora of possibilities through seamless access to shared compute and storage resources. The research proposes and conceptualizes the Multi-Agent Opportunistic Grid (MAOG) solution in an Information and Communication Technologies for Development (ICT4D) initiative to address some limitations prevalent in traditional distributed system implementations. Proof-of-concept software components based on JADE (Java Agent Development Framework) validated Multi-Agent Systems (MAS) as an important tool for provisioning of Opportunistic Grid Computing platforms. Exploration of agent technologies within the research context identified two key components which improve access to extended computer capabilities. The first component is a Mobile Agent (MA) compute component in which a group of agents interact to pool shared processor cycles. The compute component integrates dynamic resource identification and allocation strategies by incorporating the Contract Net Protocol (CNP) and rule based reasoning concepts. The second service is a MAS based storage component realized through disk mirroring and Google file-system’s chunking with atomic append storage techniques. This research provides a candidate Opportunistic Grid Computing platform design and implementation through the use of MAS. Experiments conducted validated the design and implementation of the compute and storage services. From results, support for processing user applications; resource identification and allocation; and rule based reasoning validated the MA compute component. A MAS based file-system that implements chunking optimizations was considered to be optimum based on evaluations. The findings from the undertaken experiments also validated the functional adequacy of the implementation, and show the suitability of MAS for provisioning of robust, autonomous, and intelligent platforms. The context of this research, ICT4D, provides a solution to optimizing and increasing the utilization of computing resources that are usually idle in these contexts

Intelligent wireless web services: context-aware computing in construction-logistics supply chain

The construction industry has incurred a considerable amount of waste as a result of poor logistics supply chain network management. Therefore, managing logistics in the construction industry is critical. An effective logistic system ensures delivery of the right products and services to the right players at the right time while minimising costs and rewarding all sectors based on value added to the supply chain. This paper reports on an on-going research study on the concept of context-aware services delivery in the construction project supply chain logistics. As part of the emerging wireless technologies, an Intelligent Wireless Web (IWW) using context-aware computing capability represents the next generation ICT application to construction-logistics management. This intelligent system has the potential of serving and improving the construction logistics through access to context-specific data, information and services. Existing mobile communication deployments in the construction industry rely on static modes of information delivery and do not take into account the worker’s changing context and dynamic project conditions. The major problems in these applications are lack of context-specificity in the distribution of information, services and other project resources, and lack of cohesion with the existing desktop based ICT infrastructure. The research works focus on identifying the context dimension such as user context, environmental context and project context, selection of technologies to capture context-parameters such wireless sensors and RFID, selection of supporting technologies such as wireless communication, Semantic Web, Web Services, agents, etc. The process of integration of Context-Aware Computing and Web-Services to facilitate the creation of intelligent collaboration environment for managing construction logistics will take into account all the necessary critical parameters such as storage, transportation, distribution, assembly, etc. within off and on-site project