N etwork function virtualization (NFV) is an enabling technology for telecommunication operators to achieve flexible service deployment and efficient reuse of physical resources; operators are no longer restricted to dedicated hardware and can run their services on off-the-shelf servers. However, there has been little research effort on optimizing NFV for heterogeneous multicore architectures such as ARM's big. LITTLE technology and Intel's Performance Hybrid Architecture. In this paper, we consider CPU core affinity of virtual network functions (VNFs) and study load-balancing and prudent deployment of VNFs in a heterogeneous multicore system. We not only develop the Four-Class Filling (FCF) algorithm with a complexity of O (n log n) and an approximation ratio of 3/4, but also implement it on an NFV platform equipped with two types of CPU cores. Real-world measurement validates feasibility and effectiveness of our method. Besides, simulation results show that our algorithm performs very well in terms of load-balancing factor, operational cost, and excess usage.

SUMMARY The popularity of multimedia applications made them a major theme in embedded systems. The key component for supporting multimedia application well is embedded processor. Thus, we have designed and implemented an embedded processor, called UniDual processor, to achieve this objective. Its key features are the integration of instructions of reduced instruction set computers (RISCs) and digital signal processors (DSPs) as well as the support of special instruction set and shared‐based clustered register architecture. However, an important issue of UniDual that remains open is how to efficiently allocate registers. In this paper, we present a scheduling and instruction transformation approach to resolve the aforementioned issue. The proposed approach schedules instructions and then transforms overlapped instructions into RISC and DSP instructions by taking communication overhead and hardware limitations into account. Compared with the greedy approach, the evaluation shows that our work is relatively effective in performance and code size reduction. Copyright © 2012 John Wiley & Sons, Ltd.

As power density increases with high technology, the high temperature has threatened the system performance, reliability, and even system safety. Development of a thermal management method to reduce hotspot and to balance the temperature distribution has become an important issue. Therefore, dynamic thermal management (DTM) has emerged as an effective technique for guaranteeing thermal safety. It has been getting more popular for its low cost and flexibility. In this paper, we propose a proactive thermal management scheme on the Criti-core platform, in advance using thermal-aware thread scheduling to avoid high temperature. In addition, we using thread migration mechanism when core reach a critical threshold, to increase the reliability of the system.

This paper describes a new approach to keep a moving target into the field of view of a robot, despite obstacles. Unlike previous work, this approach does not assume that a complete or partial model of the target's behavior is available, nor that a map of the obstacles is given. At approximately 10 IIz, the robot constructs a local map of the environment from range data, localizes the target in this map, and computes its new velocity command. This command is selected to minimize a function that measures the risk that the target may escape the robot's field of view by crossing an occlusion ray created by an obstacle. The risk function defined in this paper combines a reactive term, whose minimization handles immediate threats, and a look-ahead term, whose minimization improves the robot's future ability to react to evading motions of the target. The experimental robotic system has been remarkably successful at tracking a target performing brisk maneuvers and swift turns behind obstacles.

Many applications require continuous monitoring of a moving target by a controllable vision system. Although the goal of tracking objects is not new, traditional techniques usually ignore the presence of obstacles and focus on imaging and target recognition issues. For a target moving among obstacles, the goal of tracking involves a complex motion problem: a controllable observer must anticipate that the target may become occluded by an obstacle and move to prevent such an event from occurring. The paper describes a strategy for computing the motions of a mobile robot operating in a 2-D workspace without prior knowledge of the target's intention or the distribution of obstacles in the scene. The proposed algorithm governs the motion of the observer based on current measurements of the target's position and the location of the local obstacles. The approach is combinatorial in the sense that the algorithm explicitly computes a description of the geometric arrangement between the target and the observer's visibility region produced by the local obstacles. The algorithm computes a continuous control law based on this description. The new tracking strategy has been implemented in a real-time robotic system.