Recently, several parallel frameworks have emerged to utilize the increasing computational capacity of multiprocessors. Parallel tasks are distinguished from traditional sequential tasks in that the subtasks contained in a single parallel task can simultaneously execute on multiple processors. In this study, we consider the scheduling problem of minimizing the number of processors on which the parallel real-time tasks feasibly run. In particular, we focus on scheduling sporadic parallel real-time tasks, in which precedence constraints between subtasks of each parallel task are expressed using a directed acyclic graph (DAG). To address the problem, we formulate an optimization problem that aims to minimize the maximum processing capacity for executing the given tasks. We then suggest a polynomial solution consisting of three steps: (1) transform each parallel real-time task into a series of multithreaded segments, while respecting the precedence constraints of the DAG; (2) selectively extend the segment lengths; and (3) interpret the problem as a flow network to balance the flows on the terminal edges. We also provide the schedulability bound of the proposed solution: it has acapacity augmentation boundof 2. Our experimental results show that the proposed approach yields higher performance than one developed in a recent study.

Directional antennas offer many potential advantages for wireless networks such as increased network capacity, extended transmission range and reduced energy consumption. Exploiting these advantages, however, requires new protocols and mechanisms at various communication layers to intelligently control the directional antenna system. With directional antennas, many trivial mechanisms, such as neighbor discovery, become more challenging since communicating parties must agree on where and when to point their directional beams to enable communication. In this paper, we propose a fully directional neighbor discovery protocol called Sectored-Antenna Neighbor Discovery (SAND) protocol. SAND is designed for sectored-antennas, a low-cost and simple realization of directional antennas, that utilize multiple limited beamwidth antennas. Unlike many proposed directional neighbor discovery protocols, SAND depends neither on omnidirectional antennas nor on time synchronization. In addition, SAND performs neighbor discovery in a serialized fashion allowing individual nodes to discover all potential neighbors within a predetermined time. Moreover, SAND guarantees the discovery of the best sector combination on both communication ends allowing more robust and higher reliability links. Finally, SAND gathers the neighborhood information in a centralized location, if needed, to be used by centralized networking protocols. The effectiveness of SAND has been assessed via simulation studies and real hardware implementation.