Social-aware hybrid mobile offloading

Mobile offloading is a promising technique to aid the constrained resources of a mobile device. By offloading a computational task, a device can save energy and increase the performance of the mobile applications. Unfortunately, in existing offloading systems, the opportunistic moments to offload a task are often sporadic and short-lived. We overcome this problem by proposing a social-aware hybrid offloading system (HyMobi), which increases the spectrum of offloading opportunities. As a mobile device is always co- located to at least one source of network infrastructure throughout of the day, by merging cloudlet, device-to-device and remote cloud offloading, we increase the availability of offloading support. Integrating these systems is not trivial. In order to keep such coupling, a strong social catalyst is required to foster user's participation and collaboration. Thus, we equip our system with an incentive mechanism based on credit and reputation, which exploits users' social aspects to create offload communities. We evaluate our system under controlled and in-the-wild scenarios. With credit, it is possible for a device to create opportunistic moments based on user's present need. As a result, we extended the widely used opportunistic model with a long-term perspective that significantly improves the offloading process and encourages unsupervised offloading adoption in the wild

Enable Reliable and Secure Data Transmission in Resource-Constrained Emerging Networks

The increasing deployment of wireless devices has connected humans and objects all around the world, benefiting our daily life and the entire society in many aspects. Achieving those connectivity motivates the emergence of different types of paradigms, such as cellular networks, large-scale Internet of Things (IoT), cognitive networks, etc. Among these networks, enabling reliable and secure data transmission requires various resources including spectrum, energy, and computational capability. However, these resources are usually limited in many scenarios, especially when the number of devices is considerably large, bringing catastrophic consequences to data transmission. For example, given the fact that most of IoT devices have limited computational abilities and inadequate security protocols, data transmission is vulnerable to various attacks such as eavesdropping and replay attacks, for which traditional security approaches are unable to address. On the other hand, in the cellular network, the ever-increasing data traffic has exacerbated the depletion of spectrum along with the energy consumption. As a result, mobile users experience significant congestion and delays when they request data from the cellular service provider, especially in many crowded areas. In this dissertation, we target on reliable and secure data transmission in resource-constrained emerging networks. The first two works investigate new security challenges in the current heterogeneous IoT environment, and then provide certain countermeasures for reliable data communication. To be specific, we identify a new physical-layer attack, the signal emulation attack, in the heterogeneous environment, such as smart home IoT. To defend against the attack, we propose two defense strategies with the help of a commonly found wireless device. In addition, to enable secure data transmission in large-scale IoT network, e.g., the industrial IoT, we apply the amply-and-forward cooperative communication to increase the secrecy capacity by incentivizing relay IoT devices. Besides security concerns in IoT network, we seek data traffic alleviation approaches to achieve reliable and energy-efficient data transmission for a group of users in the cellular network. The concept of mobile participation is introduced to assist data offloading from the base station to users in the group by leveraging the mobility of users and the social features among a group of users. Following with that, we deploy device-to-device data offloading within the group to achieve the energy efficiency at the user side while adapting to their increasing traffic demands. In the end, we consider a perpendicular topic - dynamic spectrum access (DSA) - to alleviate the spectrum scarcity issue in cognitive radio network, where the spectrum resource is limited to users. Specifically, we focus on the security concerns and further propose two physical-layer schemes to prevent spectrum misuse in DSA in both additive white Gaussian noise and fading environments

EFFORT: Energy efficient framework for offload communication in mobile cloud computing

There is an abundant expansion in the race of technology, specifically in the production of data, because of the smart devices, such as mobile phones, smart cards, sensors, and Internet of Things (IoT). Smart phones and devices have undergone an enormous evolution in a way that they can be used. More and more new applications, such as face recognition, augmented reality, online interactive gaming, and natural language processing are emerging and attracting the users. Such applications are generally data intensive or compute intensive, which demands high resource and energy consumption. Mobile devices are known for the resource scarcity, having limited computational power and battery life. The tension between compute/data intensive application and resource constrained mobile devices hinders the successful adaption of emerging paradigms. In the said perspective, the objective of this paper is to study the role of computation offloading in mobile cloud computing to supplement mobile platforms ability in executing complex applications. This paper proposes a systematic approach (EFFORT) for offload communication in the cloud. The proposed approach provides a promising solution to partially solve energy consumption issue for communication-intensive applications in a smartphone. The experimental study shows that our proposed approach outperforms its counterparts in terms of energy consumption and fast processing of smartphone devices. The battery consumption was reduced to 19% and the data usage was reduced to 16%

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications