Big Data Gears:The Data Accelator For Large Data In Mobile Networks

BigData management is merely concerned with the large-scale data, generated from the cloud, mobile computing, media accessing and many more. Based on the research survey, such as BigCache, which emphasizes on efficiently serve the data to the end-user by provisioning the large cached data at local site, thereby to benefit effective bandwidth utilization, low server load and rapid data access at low cost. To extend this work, we would like to incorporate the notion of data gears in BigData management, to accelerate the large data access in mobile networks, which consist of the small size portable devices with mobility and low resources. These lead to the many challenges such as small cache, bandwidth management, power consumption, data sharing, secured access and so no. We mainly focus on the data access and bandwidth level in BigData through providing 'Gear Architecture' for the flexibility, portability and interchangeability of the various components in BigData over mobile networks. We will target to improve the utilization through proposing data access techniques in extended ranges using BigData analytic as a Gear

Smart PIN: performance and cost-oriented context-aware personal information network

The next generation of networks will involve interconnection of heterogeneous individual networks such as WPAN, WLAN, WMAN and Cellular network, adopting the IP as common infrastructural protocol and providing virtually always-connected network. Furthermore, there are many devices which enable easy acquisition and storage of information as pictures, movies, emails, etc. Therefore, the information overload and divergent content’s characteristics make it difficult for users to handle their data in manual way. Consequently, there is a need for personalised automatic services which would enable data exchange across heterogeneous network and devices. To support these personalised services, user centric approaches for data delivery across the heterogeneous network are also required. In this context, this thesis proposes Smart PIN - a novel performance and cost-oriented context-aware Personal Information Network. Smart PIN's architecture is detailed including its network, service and management components. Within the service component, two novel schemes for efficient delivery of context and content data are proposed: Multimedia Data Replication Scheme (MDRS) and Quality-oriented Algorithm for Multiple-source Multimedia Delivery (QAMMD). MDRS supports efficient data accessibility among distributed devices using data replication which is based on a utility function and a minimum data set. QAMMD employs a buffer underflow avoidance scheme for streaming, which achieves high multimedia quality without content adaptation to network conditions. Simulation models for MDRS and QAMMD were built which are based on various heterogeneous network scenarios. Additionally a multiple-source streaming based on QAMMS was implemented as a prototype and tested in an emulated network environment. Comparative tests show that MDRS and QAMMD perform significantly better than other approaches

Hit and Bandwidth Optimal Caching for Wireless Data Access Networks

For many data access applications, the availability of the most updated information is a fundamental and rigid requirement. In spite of many technological improvements, in wireless networks, wireless channels (or bandwidth) are the most scarce resources and hence are expensive. Data access from remote sites heavily depends on these expensive resources. Due to affordable smart mobile devices and tremendous popularity of various Internet-based services, demand for data from these mobile devices are growing very fast. In many cases, it is becoming impossible for the wireless data service providers to satisfy the demand for data using the current network infrastructures. An efficient caching scheme at the client side can soothe the problem by reducing the amount of data transferred over the wireless channels. However, an update event makes the associated cached data objects obsolete and useless for the applications. Frequencies of data update, as well as data access play essential roles in cache access and replacement policies. Intuitively, frequently accessed and infrequently updated objects should be given higher preference while preserving in the cache. However, modeling this intuition is challenging, particularly in a network environment where updates are injected by both the server and the clients, distributed all over networks. In this thesis, we strive to make three inter-related contributions. Firstly, we propose two enhanced cache access policies. The access policies ensure strong consistency of the cached data objects through proactive or reactive interactions with the data server. At the same time, these policies collect information about access and update frequencies of hosted objects to facilitate efficient deployment of the cache replacement policy. Secondly, we design a replacement policy which plays the decision maker role when there is a new object to accommodate in a fully occupied cache. The statistical information collected by the access policies enables the decision making process. This process is modeled around the idea of preserving frequently accessed but less frequently updated objects in the cache. Thirdly, we analytically show that a cache management scheme with the proposed replacement policy bundled with any of the cache access policies guarantees optimum amount of data transmission by increasing the number of effective hits in the cache system. Results from both analysis and our extensive simulations demonstrate that the proposed policies outperform the popular Least Frequently Used (LFU) policy in terms of both effective hits and bandwidth consumption. Moreover, our flexible system model makes the proposed policies equally applicable to applications for the existing 3G, as well as upcoming LTE, LTE Advanced and WiMAX wireless data access networks

Data Storage and Dissemination in Pervasive Edge Computing Environments

Nowadays, smart mobile devices generate huge amounts of data in all sorts of gatherings. Much of that data has localized and ephemeral interest, but can be of great use if shared among co-located devices. However, mobile devices often experience poor connectivity, leading to availability issues if application storage and logic are fully delegated to a remote cloud infrastructure. In turn, the edge computing paradigm pushes computations and storage beyond the data center, closer to end-user devices where data is generated and consumed. Hence, enabling the execution of certain components of edge-enabled systems directly and cooperatively on edge devices. This thesis focuses on the design and evaluation of resilient and efficient data storage and dissemination solutions for pervasive edge computing environments, operating with or without access to the network infrastructure. In line with this dichotomy, our goal can be divided into two specific scenarios. The first one is related to the absence of network infrastructure and the provision of a transient data storage and dissemination system for networks of co-located mobile devices. The second one relates with the existence of network infrastructure access and the corresponding edge computing capabilities. First, the thesis presents time-aware reactive storage (TARS), a reactive data storage and dissemination model with intrinsic time-awareness, that exploits synergies between the storage substrate and the publish/subscribe paradigm, and allows queries within a specific time scope. Next, it describes in more detail: i) Thyme, a data storage and dis- semination system for wireless edge environments, implementing TARS; ii) Parsley, a flexible and resilient group-based distributed hash table with preemptive peer relocation and a dynamic data sharding mechanism; and iii) Thyme GardenBed, a framework for data storage and dissemination across multi-region edge networks, that makes use of both device-to-device and edge interactions. The developed solutions present low overheads, while providing adequate response times for interactive usage and low energy consumption, proving to be practical in a variety of situations. They also display good load balancing and fault tolerance properties.Resumo Hoje em dia, os dispositivos móveis inteligentes geram grandes quantidades de dados em todos os tipos de aglomerações de pessoas. Muitos desses dados têm interesse loca- lizado e efêmero, mas podem ser de grande utilidade se partilhados entre dispositivos co-localizados. No entanto, os dispositivos móveis muitas vezes experienciam fraca co- nectividade, levando a problemas de disponibilidade se o armazenamento e a lógica das aplicações forem totalmente delegados numa infraestrutura remota na nuvem. Por sua vez, o paradigma de computação na periferia da rede leva as computações e o armazena- mento para além dos centros de dados, para mais perto dos dispositivos dos utilizadores finais onde os dados são gerados e consumidos. Assim, permitindo a execução de certos componentes de sistemas direta e cooperativamente em dispositivos na periferia da rede. Esta tese foca-se no desenho e avaliação de soluções resilientes e eficientes para arma- zenamento e disseminação de dados em ambientes pervasivos de computação na periferia da rede, operando com ou sem acesso à infraestrutura de rede. Em linha com esta dico- tomia, o nosso objetivo pode ser dividido em dois cenários específicos. O primeiro está relacionado com a ausência de infraestrutura de rede e o fornecimento de um sistema efêmero de armazenamento e disseminação de dados para redes de dispositivos móveis co-localizados. O segundo diz respeito à existência de acesso à infraestrutura de rede e aos recursos de computação na periferia da rede correspondentes. Primeiramente, a tese apresenta armazenamento reativo ciente do tempo (ARCT), um modelo reativo de armazenamento e disseminação de dados com percepção intrínseca do tempo, que explora sinergias entre o substrato de armazenamento e o paradigma pu- blicação/subscrição, e permite consultas num escopo de tempo específico. De seguida, descreve em mais detalhe: i) Thyme, um sistema de armazenamento e disseminação de dados para ambientes sem fios na periferia da rede, que implementa ARCT; ii) Pars- ley, uma tabela de dispersão distribuída flexível e resiliente baseada em grupos, com realocação preventiva de nós e um mecanismo de particionamento dinâmico de dados; e iii) Thyme GardenBed, um sistema para armazenamento e disseminação de dados em redes multi-regionais na periferia da rede, que faz uso de interações entre dispositivos e com a periferia da rede. As soluções desenvolvidas apresentam baixos custos, proporcionando tempos de res- posta adequados para uso interativo e baixo consumo de energia, demonstrando serem práticas nas mais diversas situações. Estas soluções também exibem boas propriedades de balanceamento de carga e tolerância a faltas

Pervasive service discovery in low-power and lossy networks

Pervasive Service Discovery (SD) in Low-power and Lossy Networks (LLNs) is expected to play a major role in realising the Internet of Things (IoT) vision. Such a vision aims to expand the current Internet to interconnect billions of miniature smart objects that sense and act on our surroundings in a way that will revolutionise the future. The pervasiveness and heterogeneity of such low-power devices requires robust, automatic, interoperable and scalable deployment and operability solutions. At the same time, the limitations of such constrained devices impose strict challenges regarding complexity, energy consumption, time-efficiency and mobility. This research contributes new lightweight solutions to facilitate automatic deployment and operability of LLNs. It mainly tackles the aforementioned challenges through the proposition of novel component-based, automatic and efficient SD solutions that ensure extensibility and adaptability to various LLN environments. Building upon such architecture, a first fully-distributed, hybrid pushpull SD solution dubbed EADP (Extensible Adaptable Discovery Protocol) is proposed based on the well-known Trickle algorithm. Motivated by EADPs’ achievements, new methods to optimise Trickle are introduced. Such methods allow Trickle to encompass a wide range of algorithms and extend its usage to new application domains. One of the new applications is concretized in the TrickleSD protocol aiming to build automatic, reliable, scalable, and time-efficient SD. To optimise the energy efficiency of TrickleSD, two mechanisms improving broadcast communication in LLNs are proposed. Finally, interoperable standards-based SD in the IoT is demonstrated, and methods combining zero-configuration operations with infrastructure-based solutions are proposed. Experimental evaluations of the above contributions reveal that it is possible to achieve automatic, cost-effective, time-efficient, lightweight, and interoperable SD in LLNs. These achievements open novel perspectives for zero-configuration capabilities in the IoT and promise to bring the ‘things’ to all people everywhere

Content Replication and Placement Schemes for Wireless Mesh Networks

Recently, Wireless Mesh Networks (WMNs) have attracted much of interest from both academia and industry, due to their potential to provide an alternative broadband wireless Internet connectivity. However, due to different reasons such as multi-hop forwarding and the dynamic wireless link characteristics, the performance of current WMNs is rather low when clients are soliciting Web contents. Due to the evolution of advanced mobile computing devices; it is anticipated that the demand for bandwidth-onerous popular content (especially multimedia content) in WMNs will dramatically increase in the coming future. Content replication is a popular approach for outsourcing content on behalf of the origin content provider. This area has been well explored in the context of the wired Internet, but has received comparatively less attention from the research community when it comes to WMNs. There are a number of replica placement algorithms that are specifically designed for the Internet. But they do not consider the special features of wireless networks such as insufficient bandwidth, low server capacity, contention to access the wireless medium, etc. This thesis studies the technical challenges encountered when transforming the traditional model of multi-hop WMNs from an access network into a content network. We advance the thesis that support from packet relaying mesh routers to act as replica servers for popular content such as media streaming, results in significant performance improvement. Such support from infrastructure mesh routers benefits from knowledge of the underlying network topology (i.e., information about the physical connections between network nodes is available at mesh routers). The utilization of cross-layer information from lower layers opens the door to developing efficient replication schemes that account for the specific features of WMNs (e.g., contention between the nodes to access the wireless medium and traffic interference). Moreover, this can benefit from the underutilized resources (e.g., storage and bandwidth) at mesh routers. This utilization enables those infrastructure nodes to participate in content distribution and play the role of replica servers. In this thesis, our main contribution is the design of two lightweight, distributed, and scalable object replication schemes for WMNs. The first scheme follows a hierarchical approach, while the second scheme follows a flat one. The challenge is to replicate content as close as possible to the requesting clients and thus, reduce the access latency per object, while minimizing the number of replicas. The two schemes aim to address the questions of where and how many replicas should be placed in the WMN. In our schemes, we consider the underlying topology joint with link-quality metrics to improve the quality of experience. We show using simulation tests that the schemes significantly enhance the performance of a WMN in terms of reducing the access cost, bandwidth consumption and computation/communication cost