This work focuses on the development of an effective collision avoidance algorithm that detects and avoids obstacles autonomously in the vicinity of a potential collision by using a single ultrasonic sensor and controlling the movement of the vehicle. The objectives are to minimise the deviation from the vehicle’s original path and also the development of an algorithm utilising one of the cheapest sensors available for very lost cost systems. For instance, in a scenario where the main ranging sensor malfunctions, a backup low cost sensor is required for safe navigation of the vehicle while keeping the deviation to a minimum. The developed algorithm utilises only one ultrasonic sensor and approximates the front shape of the detected object by sweeping the sensor mounted on top of the unmanned vehicle. In this proposed approach, the sensor is rotated for shape approximation and edge detection instead of moving the robot around the encountered obstacle. It has been tested in various indoor situations using different shapes of objects, stationary objects, moving objects, and soft or irregularly shaped objects. The results show that the algorithm provides satisfactory outcomes by entirely avoiding obstacles and rerouting the vehicle with a minimal deviation.

A novel, cedar-shaped, coplanar waveguide-fed frequency reconfigurable antenna is proposed. The presented antenna uses low-cost FR4 substrate with a thickness of 1.6 mm. Four PIN diodes are inserted on the antenna surface to variate the current distribution and alter the resonant frequencies with different combinations of switches. The proposed antenna is fabricated and measured for all states, and a good agreement is seen between measured and simulated results. This antenna resonates within the range of 2 GHz to 10 GHz, covering the major wireless applications of aviation service, wireless local area network (WLAN), worldwide interoperability for microwave access (WiMAX), long distance radio telecommunications, and X-band satellite communication. The proposed antenna works resourcefully with reasonable gain, significant bandwidth, directivity, and reflection coefficient. The proposed multiband reconfigurable antenna will pave the way for future wireless communications including WLAN, WiMAX, and possibly fifth-generation (5G) communication.

Traditional methods in 3D NoCs simply use a deterministic routing algorithm to deliver packets from a source to a destination node. However, deterministic methods are unable to distribute the traffic load over the network, which results in degrading the performance. In this paper, we present a fully adaptive routing algorithm for 3D NoCs, named DyXYZ. In DyXYZ, the congestion information at the input buffer of the neighboring routers is used as congestion metric to select among the output channels. This algorithm is proven to be deadlock free by using 4, 4, and 2 virtual channels along the X, Y, and Z dimensions, respectively.

Present day market demand for high-performance high-density portable hand-held applications has shifted the focus from 2-D planar system-on-a-chip-type single-chip solutions to alternatives such as tiled silicon and single-level embedded modules as well as 3-D die stacks. Among the various choices, finding an optimal solution for system implementation deals usually with cost, performance, power, thermal, and technological tradeoff analyses at the system conceptual level. It has been estimated that decisions made in the first 20% of the design cycle influence up to 80% of the final product cost. In this paper, we discuss realistic metrics appropriate for performance and cost tradeoff analyses both at the system conceptual level in the early stages of the design cycle and in the implementation phase, for verification. In order to validate the proposed metrics and methodology, two ubiquitous electronic systems are analyzed under various implementation schemes and the performance tradeoffs discussed. This case study is used to highlight the importance of a cost and performance tradeoff analysis early in the design flow.

As the scale of a cloud data center becomes larger and larger, the energy consumption of the data center also grows rapidly. Dynamic consolidation of Virtual Machines (VMs) presents a significant opportunity to save energy by turning off unused Physical Machines (PMs) in data centers. In this paper, we present a distributed controller to perform dynamic VM consolidation to improve the resource utilizations of PMs and to reduce their energy consumption. Moreover, we use the ant colony system to find a near-optimal VM placement solution based on the specified objective function. Experimental results on the real workload traces from more than a thousand PlanetLab VMs show that the proposed approach reduces energy consumption and maintains required performance levels in a large-scale data center.