The evolution of cyber-physical system (CPS) benefits from substantial supports of many cutting-edge technologies. However, as a significant medium to bridge virtual and reality parts, the dependability of various network components is facing unprecedented challenges and threats. In this article, we propose a smart collaborative balancing (SCB) scheme to dynamically adjust the orchestration of network functions and efficiently optimize the workflow patterns. First, mathematical models of bandwidth allocation for multiuser with appropriate probability distribution are established. Matrix operations are utilized to solve the relevant issues based on individual congestion windows. Invasion defense mechanisms are also provided and discussed. Second, specific procedures of collaboration among different network components are presented. The capabilities of CPS, in terms of bandwidth allocation and invasion defense, are guaranteed via novel queueing policies and access control mechanisms. Third, we build a comprehensive prototype including multiple domains and users for validations. Experimental results in two scenarios illustrate that SCB not only supports service reliability of end hosts with different priorities, but also resists malicious attacks which are targeting the corresponding terminals inside domains. Compared to the benchmarks in software defined networks and traditional Internet, our scheme performs better in both available resource management and abnormal flow recognition aspects.

Artificial intelligence is being utilized in multipath industrial networks to enhance service supporting ability. However, existing obstacles (unexpected occupation, disordered chunks, etc.) in controlling receive buffer restrict throughput even when higher bandwidth is available. Therefore, we propose a Smart Collaborative Automation (SCA) scheme to improve resource usage. First, a mathematical model is established to describe main system operations with considerations of chunk loss. The inf-supremum and probability theory are adopted to track congestion window variations. Second, differences of disordered chunk expectation are analyzed to locate the critical condition of round number. Specific algorithm details are provided via simplifying comparison to achieve comprehensive policy selections. Third, evaluation topologies and environments are created with logical parameters settings. Validation results demonstrate that model-driven SCA can reduce unexpected occupations at the receiver-side. Comparing to intuitive-driven schemes, overall performances, in terms of sender's transmission capacity and receiver's buffer utilization, are improved under different experimental configurations.

It is knotty for current routing protocols to meet the needs of reliable data diffusion during the Internet of Things (IoT) deployments. Due to the random placement, limited resources and unattended features of existing sensor nodes, the wireless transmissions are easily exposed to unauthorized users, which becomes a vulnerable area for various malicious attacks, such as wormhole and Sybil attacks. However, the scheme based on geographic location is a suitable candidate to defend against them. This paper is inspired to propose a smart collaborative routing protocol, Geographic energy aware routing and Inspecting Node (GIN), for guaranteeing the reliability of data exchanging. The proposed protocol integrates the directed diffusion routing, Greedy Perimeter Stateless Routing (GPSR), and the inspecting node mechanism. We first discuss current wireless routing protocols from three diverse perspectives (improving transmission rate, shortening transmission range and reducing transmission consumption). Then, the details of GIN, including the model establishment and implementation processes, are presented by means of the theoretical analysis. Through leveraging the game theory, the inspecting node is elected to monitor the network behaviors. Thirdly, we evaluate the network performances, in terms of transmission delay, packet loss ratio, and throughput, between GIN and three traditional schemes (i.e., Flooding, GPSR, and GEAR). The simulation results illustrate that the proposed protocol is able to outperform the others.

The significant changes enabled by the fog computing had demonstrated that Internet of Things (IoT) urgently needs more evolutional reforms. Limited by the inflexible design philosophy; the traditional structure of a network is hard to meet the latest demands. However, Information-Centric Networking (ICN) is a promising option to bridge and cover these enormous gaps. In this paper, a Smart Collaborative Caching (SCC) scheme is established by leveraging high-level ICN principles for IoT within fog computing paradigm. The proposed solution is supposed to be utilized in resource pooling, content storing, node locating and other related situations. By investigating the available characteristics of ICN, some challenges of such combination are reviewed in depth. The details of building SCC, including basic model and advanced algorithms, are presented based on theoretical analysis and simplified examples. The validation focuses on two typical scenarios: simple status inquiry and complex content sharing. The number of clusters, packet loss probability and other parameters are also considered. The analytical results demonstrate that the performance of our scheme, regarding total packet number and average transmission latency, can outperform that of the original ones. We expect that the SCC will contribute an efficient solution to the related studies.

The issues of energy supply had been widely investigated to upgrade the network lifetime, power utilization, and system stability of communication networks. However, the deployable charging solution for massive mobile terminals in 5G is still lack. Although prior studies in wireless rechargeable sensor networks focused on the energy usage effectiveness, the charging time was frequently overlooked in most schemes. In this paper, we propose a novel distributed mobile charging (DMC) algorithm to optimize the charging time and charger quantity. The traditional policies are first analyzed based on the energy source. We noticed that the location of base station is extremely significant for charging performance. Then, the details of the DMC algorithm are illustrated through the main process of energy transfer, formula deductions, and performance optimization. To further promote the network capacity, an improved algorithm named adaptive dynamic energy transfer is proposed by introducing linear node sleeping mechanism. The simulation results demonstrate that the algorithms are able to improve the charging time and charger quantity in multiple scenarios.

The emergence of the 5G network has brought broad prospects for the massive terminal access and ubiquitous Internet of Things (IoTs). Potential attacking opportunities triggered by this progress are severely impacting the security fortress of current networks, especially in the edge access part. However, due to the unitary protection and inferior isolation, available security schemes are incapable of effectively eliminating these hidden perils. Motivated by these facts, we propose a Multi-dimensional Fine-grained Control (MFC) framework to strengthen safety and reliability in Radio Access Networks (RANs). First, we comprehensively survey and summarize the existing security schemes to grasp respective effects and limitations. Second, the MFC framework is established to describe the model structure and implementation processes. An identifier mapping mechanism is designed to achieve network isolation. We perform the security analysis of MFC by theoretically comparing diversified policies. Third, an integrated set of the authentication prototype system is created with wireless environment parameters settings. Specific verification scenarios are illustrated. Finally, we test the performances of the MFC framework. Validation results demonstrate that the proposed scheme can accomplish reliable security control at the access side. Comparing to multiple schemes, the performances, in terms of time and concurrency, are optimized. Therefore, the MFC framework is feasible for applications in 5G or IoT.