DESIGN AND DEVELOPMENT OF CARRIER ASSIGNMENT AND PACKET SCHEDULING IN LTE-A AND Wi-Fi

The highly competitive environment in today's wireless and cellular network industries is making the management of systems seek for better and more advance techniques to keep masses of data, complexity of systems and deadline constrains under control with a lower cost and higher efficiency. Therefore, the management is getting significant attentions by researchers in order to increase the efficiency of the resource usage to provide high quality services. Two of the cornerstones of the management system in wireless and cellular network are carrier assignment and packet scheduling. Therefore, this work focuses on analysis and development of carrier assignment and packet scheduling methods in multi-band Wi-Fi and LTE-A networks. First, several existing carrier assignment methods which are developed by considering different strategists in LTE and LTE-A are analyzed. Secondly, a new technique for the carrier assignment methods for LTE and LTE-A is developed to improve the efficiency of carrier assignment methods. Thirdly, a novel carrier assignment method is proposed by considering the behaviors of mobile users for LTE and LTE-A. Then, a novel architecture with packet scheduling scheme is proposed for next generation mobile routers in multi-band Wi-Fi environment as similar to LTE-A. Finally, the scheme is improved based on energy awareness. Results show that the developed methods improve the performance of the systems in comparison to existing methods. The proposed methods and related analysis should help network engineers and service providers build next generation carrier assignment and packet scheduling methods to satisfy users in LTE, LTE-A and Wi-Fi

Trade-off Model of Fog-Cloud Computing for Space Information Networks

A steadily growing number of Internet-based service requests from the IoT has led to an increase in complexity and number of clients, resulting in an increased number of cybersecurity concerns. Although there are main security concerns with IoT services over cloud computing services, cloud computing is mostly preferred to provide seamless and scalable Intern-based services. Moreover, cloud service providers are continuously extending their capacity to reach more industries and address their concerns. For example, Amazon has recently launched a pay-as-you-go cloud computing service that will take place on satellite operators to provide more IoT services to industries such as the agricultural and shipping industries. However, the secure transfer of information within a space information network is of great concern due to the ability of numerous attacks between nodes to occur. This can be followed by loss of data Confidentiality, Integrity, and Availability. Several researchers have proposed multifaceted solutions to these concerns, including blockchain application, digital signature, and symmetric/asymmetric encryption schemes, and centralized and/or decentralized key management for space information networks. In this paper, we focus on the integration of fog-cloud computing and space information network. We primarily investigate the feasibility of fogcloud architecture in space information networks and the benefits of having fog computing in the security of space information networks. This is accomplished mainly by reviewing existing works on fog-cloud computing and space information networks, as well as evaluating both proposed solutions to potential issues regarding security

A Survey Of Mobile Crowdsensing Techniques

Mobile crowdsensing serves as a critical building block for emerging Internet of Things (IoT) applications. However, the sensing devices continuously generate a large amount of data, which consumes much resources (e.g., bandwidth, energy, and storage) and may sacrifice the Quality-of-Service (QoS) of applications. Prior work has demonstrated that there is significant redundancy in the content of the sensed data. By judiciously reducing redundant data, data size and load can be significantly reduced, thereby reducing resource cost and facilitating the timely delivery of unique, probably critical information and enhancing QoS. This article presents a survey of existing works on mobile crowdsensing strategies with an emphasis on reducing resource cost and achieving high QoS. We start by introducing the motivation for this survey and present the necessary background of crowdsensing and IoT. We then present various mobile crowdsensing strategies and discuss their strengths and limitations. Finally, we discuss future research directions for mobile crowdsensing for IoT. The survey addresses a broad range of techniques, methods, models, systems, and applications related to mobile crowdsensing and IoT. Our goal is not only to analyze and compare the strategies proposed in prior works, but also to discuss their applicability toward the IoT and provide guidance on future research directions for mobile crowdsensing