6908345
A swarm intelligence routing algorithm for MANETs
This paper presents a novel swarm intelligence inspired routing algorithm (EARA) for mobile ad hoc networks. Based on the understanding of the evolutionary cooperation in the biological swarm, which provides an alternative solution resilient against changes in the dynamic environment, We use the principle of swarm intelligence for the reinforcement of optimal routes with only local communication (here, local communication is defined as neighbourto-neighbour one only). The data traffic is influenced at each node, and the communicating nodes observe this influence to update their tables. We also include an evaluation, and the simulation results show that this routing algorithm scales well to a variety of network conditions.
8433230
A biologically inspired congestion control routing algorithm for MANETs
This paper presents EARA-CG, an improved version of a swarm-intelligence ad hoc routing algorithm EARA introduced in the work of Z. Liu et al. (2004). Based on the understanding of the evolutionary cooperation in the biological swarm, we use the principle of swarm intelligence to reinforce good quality routes with only local communication. The concept of stigmergy is adopted to reduce the amount of control traffic. By locally monitoring the network transmission queue and other MAC layer information, this algorithm can forward data traffic through paths that avoid network hotspots. The data traffic influences routing table updates at each node. We also discuss an evaluation methodology to simulate ad hoc networks, and the simulation results show that this novel routing algorithm scales well to a variety of network conditions.
6770113
Image magnification method using joint diffusion
In this paper a new algorithm for image magnification is presented. Because linear magnification/interpolation techniques diminish the contrast and produce sawtooth effects, in recent years, many nonlinear interpolation methods, especially nonlinear diffusion based approaches, have been proposed to solve these problems. Two recently proposed techniques for interpolation by diffusion, forward and backward diffusion (FAB) and level-set reconstruction (LSR), cannot enhance the contrast and smooth edges simultaneously. In this article, a novel Partial Differential Equations (PDE) based approach is presented. The contributions of the paper include: firstly, a unified form of diffusion joining FAB and LSR is constructed to have all of their virtues; secondly, to eliminate artifacts of the joint diffusion, soft constraint takes the place of hard constraint presented by LSR; thirdly, the determination of joint coefficients, criterion for stopping time and color image processing are also discussed. The results demonstrate that the method is visually and quantitatively better than Bicubic, FAB and LSR.
5135154
Linking UML models of design and requirement
Both a UML model of requirement and a UML model of a design are defined as a pair of class diagram and a family of sequence diagrams. We then give an unified semantics for models of requirements and designs. We define the consistency between a design class diagram and the interaction diagrams and show how the removal of inconsistency can be treated as a model refinement. We then formally define the correctness of UML model of design with respect to the model of requirement.
16274304
Face detection and tracking in video using dynamic programming
Face detection and tracking are important in video content analysis since the most important objects in most video are human beings. This paper proposes a new approach for combined face detection and tracking in video. The face detection algorithm is a fast template matching procedure using iterative dynamic programming (DP). Although the face detection algorithm is designed for frontal face, the same mechanism can also be applied to track non-frontal faces with online adapted face models. Due to the essence of template matching, the algorithm is capable of comparing the similarity among different faces, which makes it suitable for tracking the same face that occur at disjointed temporal locations in video. While the proposed face detection method provides comparable accuracy as the neural network based approach, it is much faster.
12816052
Worst-Case Analysis of Scheduling Heuristics of Parallel Systems
Abstract It is well-known that most scheduling problems arising from parallel systems are NP -hard, even under very special assumptions. Thus, various suboptimal algorithms, in particular heuristics, were proposed in the literature. Worst-case error bounds are established in this paper for heuristics of makespan minimization of parallel computations. Different parallel computation models are investigated, including interprocessor communication, task duplication, multiprocessor tasks and parallel tasks. Due to the heterogeneity of these systems, scheduling heuristics can be far away from the optimal solutions. These bounds provide insights to the design of scheduling heuristics in order to obtain good performance guarantee than arbitrary heuristics. Moreover, the performance guarantee of these special heuristics is independent of model parameters such as the maximal duplication degree, processor requirement and parallelization degree.
11533242
Multi-robot mobility enhanced hop-count based localization in ad hoc networks
The localization problem is important in mobile robots and wireless sensor network and has been studied for many years. Among many localization methods, the hop-count based approach is simple and scalable; however, the localization accuracy is not satisfactory if the node density is low. To solve this problem, in this paper a multi-robot approach is proposed to utilize the cooperation and mobility of the robots to improve the node distribution (density), thus enhancing the hop-count based localization. By an auction-based task allocation scheme, the robots can negotiate with the static sensor nodes and then select the most suitable robots to move to the area of sparse node density, thus increasing the localization accuracy for the static sensor nodes. On the other hand, the robots also can localize themselves with the help of the static sensor nodes. The efficacy of this approach is shown by simulation.