Power Aware Routing in Mobile Ad Hoc Networks

A fast image encryption algorithm based on chaotic map

Emotions appear to be a key determinant of behavior in cooperative relationships. Emotions affect behavior both directly, by motivating action, and indirectly, as actors anticipate others’ emotional responses. The influence of emotions is understandable once it is recognized that (a) the ability to benefit from cooperative relationships has been a key determinant of biological fitness throughout our species’ history, and (b) panhuman emotions are adaptations crafted by natural selection. Different emotions affect cooperative behavior in different ways: some emotions lead actors to forego the temptation to defect, some lead them to reciprocate harm suffered or benefits provided, and some lead them to repair damaged relationships. An important class of emotions influences cooperative behavior in part by motivating conformity to norms and/or punishment of norm violators. This chapter discusses thirteen emotions that seem to have the greatest impact on cooperation. In addition to reviewing empirical evidence of the role of emotions in cooperation, the chapter presents a variety of explanatory hypotheses and provides a number of discrete testable predictions.

Genetic and cultural evolution of cooperation

Four relations are defined the use of which allow a reliability network to be expressed as a mathematical statement. Series and active and standby redundancy connections are allowed. The possibility of requiring more than one of the active branches to be operative is included. At the very least the result allows for typing in place of drawing a network description.

http://ieeexplore.ieee.org/iel5/24/5216426/05216446.pdf

Network Calculus

A hyper-chaos-based image encryption algorithm using pixel-level permutation and bit-level permutation

This paper presents an efficient and secure chaotic S-Box based image encryption algorithm. Firstly, by cryptanalyzing a multiple chaotic S-Boxes based image encryption algorithm, we successfully cracked the cryptosystem by using chosen-plaintext attack (CPA). Secondly, we put forward a new image encryption scheme based on a novel compound chaotic map and single S-Box. In the new scheme, a novel discrete compound chaotic system, Logistic-Sine system (LSS), is proposed, which has wider chaotic range and better chaotic properties. And a new S-Box is constructed by using LSS, which has satisfactory cryptographic performance. Based on the new S-Box and the chaotic key stream, the new image encryption algorithm is designed, which consist of a round of permutation and two rounds of substitution process. The permutation and substitution key sequences are related to the plaintext image content, this strategy enables the cryptosystem to resist CPA. The simulation results and security analysis verified the effectiveness of the proposed image encryption scheme. Especially, the new scheme has obvious efficiency advantages, showing that it has better application potential in real-time image encryption.

/pdf/an-efficient-image-encryption-scheme-based-on-the-lss-3ebq3pvgl1.pdf

An Efficient Image Encryption Scheme Based on the LSS Chaotic Map and Single S-Box

Energy harvesting (EH) from ambient energy sources can potentially reduce the dependence on the supply of grid or battery energy, providing many benefits to green communications. In this paper, we investigate the device-to-device (D2D) user equipments (DUEs) multiplexing cellular user equipments (CUEs) downlink spectrum resources problem for EH-based D2D communication heterogeneous networks (EH-DHNs). Our goal is to maximize the average energy efficiency of all D2D links, in the case of guaranteeing the quality of service of CUEs and the EH constraints of the D2D links. The resource allocation problems contain the EH time slot allocation of DUEs, power and spectrum resource block (RB) allocation. In order to tackle these issues, we formulate an average energy efficiency problem in EH-DHNs, taking into consideration EH time slot allocation, power and spectrum RB allocation for the D2D links, which is a nonconvex problem. Furthermore, we transform the original problem into a tractable convex optimization problem. We propose joint the EH time slot allocation, power and spectrum RB allocation iterative algorithm based on the Dinkelbach and Lagrangian constrained optimization. Numerical results demonstrate that the proposed iterative algorithm achieves higher energy efficiency for different network parameters settings.

Energy Efficient Resource Allocation Algorithm in Energy Harvesting-Based D2D Heterogeneous Networks

Cooperative channel allocation and scheduling are key issues in wireless mesh networks with multiple interfaces and multiple channels. In this paper, we propose a load balance link layer protocol (LBLP) aiming to cooperatively manage the interfaces and channels to improve network throughput. In LBLP, an interface can work in a sending or receiving mode. For the receiving interfaces, the channel assignment is proposed considering the number, position and status of the interfaces, and a task allocation algorithm based on the Huffman tree is developed to minimize the mutual interference. A dynamic link scheduling algorithm is designed for the sending interfaces, making the tradeoff between the end-to-end delay and the interface utilization. A portion of the interfaces can adjust their modes for load balancing according to the link status and the interface load. Simulation results show that the proposed LBLP can work with the existing routing protocols to improve the network throughput substantially and balance the load even when the switching delay is large.

Cooperative channel allocation and scheduling in multi-interface wireless mesh networks

Remote clouds are gradually unable to achieve ultra-low latency to meet the requirements of mobile users because of the intolerable long distance between remote clouds and mobile users and the network congestion caused by the tremendous number of users. Mobile edge computing, a new paradigm, has been proposed to mitigate aforementioned effects. Existing studies mostly assume the edge servers have been deployed properly and they just pay attention to how to minimize the delay between edge servers and mobile users. In this paper, considering the practical environment, we investigate how to deploy edge servers effectively and economically in wireless metropolitan area networks. Thus, we address the problem of minimizing the number of edge servers while ensuring some QoS requirements. Aiming at more consistence with a generalized condition, we extend the definition of the dominating set, and transform the addressed problem into the minimum dominating set problem in graph theory. In addition, two conditions are considered for the capacities of edge servers: one is that the capacities of edge servers can be configured on demand, and the other is that all the edge servers have the same capacities. For the on-demand condition, a greedy based algorithm is proposed to find the solution, and the key idea is to iteratively choose nodes that can connect as many other nodes as possible under the delay, degree and cluster size constraints. Furthermore, a simulated annealing based approach is given for global optimization. For the second condition, a greedy based algorithm is also proposed to satisfy the capacity constraint of edge servers and minimize the number of edge servers simultaneously. The simulation results show that the proposed algorithms are feasible.

/pdf/cost-effective-edge-server-placement-in-wireless-t974aye72n.pdf

Cost-Effective Edge Server Placement in Wireless Metropolitan Area Networks

Geographic routing is a research hotspot of the Internet of Vehicles (IoV) and intelligent traffic system (ITS). In practice, the vehicle movement is not only affected by its characteristics and the relationship between the vehicle and position but also affected by some implicit factors. Pointing to this problem, we combine the vehicle moving position probability matrix, the vehicle position association matrix, and the implicit factors to study the influence of vehicle position potential features and vehicle association potential features and propose a routing algorithm based on vehicle position (RAVP) analysis, which can obtain the more accurate vehicle prediction trajectory. Then, the vehicle distance is obtained based on the vehicle prediction trajectory. By the normalization of vehicle distance and cache, the vehicle data forwarding capability is obtained and the transmission decision is made. Simulation results show that the proposed algorithm outperforms the other three routing algorithms in terms of packet delivery ratio, average end-to-end delay, and routing overhead ratio.

Xiaoheng Deng

Papers

An Efficient Image Encryption Scheme Based on the LSS Chaotic Map and Single S-Box

Energy Efficient Resource Allocation Algorithm in Energy Harvesting-Based D2D Heterogeneous Networks

Cooperative channel allocation and scheduling in multi-interface wireless mesh networks

Cost-Effective Edge Server Placement in Wireless Metropolitan Area Networks

Routing Algorithm Based on Vehicle Position Analysis for Internet of Vehicles