Biblio

Fog-Cloud framework is being regarded as a more promising technology to provide performance guarantee for IoT applications, which not only have higher requirements on computation resources, but also are delay and/or security sensitive. In this framework, a delay and security-sensitive computation task is usually divided into several sub-tasks, which could be offloaded to either fog or cloud computing servers, referred to as offloading destinations. Sub-tasks may exchange information during their processing and then have requirement on transmission bandwidth. Different destinations produce different completion delays of a sub-task, affecting the corresponding task delay. The existing offloading approaches either considered only a single type of offloading destinations or ignored delay and/or security constraint. This paper studies a computation offloading problem in the fog-cloud scenario where not only computation and security capabilities of offloading destinations may be different, but also bandwidth and delay of links may be different. We first propose a joint offloading approach by formulating the problem as a form of Mixed Integer Programming Multi-Commodity Flow to maximize the fog-cloud provider's revenue without sacrificing performance and security requirements of users. We also propose a greedy algorithm for the problem. Extensive simulation results under various network scales show that the proposed computation offloading mechanism achieves higher revenue than the conventional single-type computation offloading under delay and security constraints.

The growing interest in the smart device/home/city has resulted in increasing popularity of Internet of Things (IoT) deployment. However, due to the open and heterogeneous nature of IoT networks, there are various challenges to deploy an IoT network, among which security and scalability are the top two to be addressed. To improve the security and scalability for IoT networks, we propose a Software-Defined Virtual Private Network (SD-VPN) solution, in which each IoT application is allocated with its own overlay VPN. The VPN tunnels used in this paper are VxLAN based tunnels and we propose to use the SDN controller to push the flow table of each VPN to the related OpenvSwitch via the OpenFlow protocol. The SD-VPN solution can improve the security of an IoT network by separating the VPN traffic and utilizing service chaining. Meanwhile, it also improves the scalability by its overlay VPN nature and the VxLAN technology.

With the scale of big data increasing in large-scale IoT application, fog computing is a recent computing paradigm that is extending cloud computing towards the edge of network in the field. There are a large number of storage resources placed on the edge of the network to form a geographical distributed storage system in fog computing system (FCS). It is used to store the big data collected by the fog computing nodes and to reduce the management costs for moving big data to the cloud. However, the storage of fog nodes at the edge of the network faces a direct attack of external threats. In order to improve the security of the storage of fog nodes in FCS, in this paper, we proposed a data security storage model for fog computing (FCDSSM) to realize the integration of storage and security management in large-scale IoT application. We designed a detail of the FCDSSM system architecture, gave a design of the multi-level trusted domain, cooperative working mechanism, data synchronization and key management strategy for the FCDSSM. Experimental results show that the loss of computing and communication performance caused by data security storage in the FCDSSM is within the acceptable range, and the FCDSSM has good scalability. It can be adapted to big data security storage in large-scale IoT application.

IoT (Internet of Things) is a network of interconnected devices, designed to collect and exchange data which can then turn it into information, eventually into wisdom. IoT is a region where digital world converges with physical world. With the evolution of IoT, it is expected to create substantial impact on human lives. IoT ecosystem produces and exchanges sizeable data due to which IoT becomes an attractive target for adversary. The large-scale interconnectivity leads to various potential risk related to information security. Security assurance in IoT ecosystem is one of the major challenges to address. In this context, embedded security becomes a key issue in IoT devices which are constrained in terms of processing, power, memory and bandwidth. The focus of this paper is on the recommended design considerations for constrained IoT devices with the objective to achieve security by default. Considering established set of protocols along with best practices during design and development stage can address majority of security challenges.

The design of low power chip for IoT applications is very challenge, especially for self-powered wireless sensors. Achieving ultra low power requires both system level optimization and circuit level innovation. This paper presents a continuous-in-time and discrete-in-amplitude (CTDA) system architecture that facilitates adaptive data rate sampling and clockless implementation for a wireless sensor SoC.