14114624
A metric and mixed-integer-programming-based approach for resource allocation in dynamic real-time systems
Dynamic real-time systems such as embedded systems operate in environments in which several parameters vary at run time. These systems must satisfy several performance requirements. Resource allocation on these systems becomes challenging because variations of run-time parameters may cause violations of the performance requirements. Performance violations result in the need for dynamic re-allocation, which is a costly operation. A method for allocating resources such that the allocation can sustain the system in the light of a continuously changing environment is developed. We introduce a novel performance metric called MAIL (maximum allowable increase in load) to capture the effectiveness of a resource allocation. Given a resource allocation, MAIL quantifies the amount of additional load that can be sustained by the system without any performance violations. A mixed-integer-programming-based approach (MIP) is developed to determine a resource allocation that has the highest MAIL value. Using simulations, several sets of experiments are conducted to evaluate our heuristics in various scenarios of machine and task heterogeneities. The performance of MIP is compared with three other heuristics: integer-programming based, greedy, and classic min-min. Our results show that MIP performs significantly better when compared with the other heuristics.
6083994
On communication models for algorithm design in networked sensor systems: A case study,
Towards building a systematic methodology of algorithm design for applications of networked sensor systems, we formally define two link-wise communication models, the Collision Free Model (CFM) and the Collision Aware Model (CAM). While CFM provides ease of programming and analysis for high level application functionality, CAM enables more accurate performance analysis and hence more efficient algorithms through cross-layer optimization, at the expense of increased programming and analysis complexity. These communication models are part of an abstract network model, above which algorithm design and performance optimization is performed. We use the example of optimizing a probability based broadcasting scheme under CAM to illustrate algorithm optimization based on the defined models. Specifically, we present an analytical framework that facilitates an accurate modeling and analysis for the probability based broadcasting in CAM (PB_CAM). Our analytical results indicate that (1) the optimal broadcast probability for either maximizing the reachability within a given latency constraint or minimizing the latency for a given reachability constraint decreases rapidly with node density, and (2) the optimal probability for either maximizing the reachability with a given energy constraint or minimizing the energy cost for a given reachability constraint varies slowly between 0 and 0.1 over the entire range of the variations in node density. Our analysis is also confirmed by extensive simulation results.
17009533
Utility-Driven Spatiotemporal Sampling Using Mobile Sensors
Many real-world applications for sensor networks require event sampling with sufficient resolution over both spatial and temporal dimensions. When the deployed nodes are insufficient to fully cover the sensor field to satisfy this spatiotemporal sampling requirements of all events, nodes with intelligent mobility are crucial to improve the sampling quality. We measure the sampling quality using a utility function that incorporates both the importance and spatiotemporal properties of events. We then describe a Utility Driven Mobility (UDM) scheme, which enables autonomous mobility scheduling of nodes in a distributed fashion. We evaluate the performance of UDM via extensive simulation studies. Our work provides a practical framework for spatiotemporal sampling using mobile sensor networks.
14893914
Energy-balanced task allocation for collaborative processing in networked embedded systems
In this paper, we study the problem of allocating a real-time application onto a set of homogeneous processing elements connected by a single-hop wireless network. A periodic application consisting of a set of communicating tasks is considered. Each element is equipped with discrete dynamic voltage scaling for exploring the energy-latency tradeoffs. The time and energy costs of both computation and communication activities are considered. The goal is to balance the energy dissipation of the elements during each period of the application with respect to the remaining energy of elements, such that the system lifetime is maximized. An Integer Linear Programming (ILP) formulation is first developed, which can be solved to obtain the optimal solution. We then propose an efficient 3-phase heuristic. Experimental results show that for small scale problems, the performance of the heuristic achieves up to 85% of the system lifetime obtained by the ILP-based approach. For large scale problems, the performance of the heuristic shows an improvement of 120-250\% in the system lifetime compared with the case where no voltage scaling is used. Further, we present two extensions of our approaches that consider multiple communication channels and techniques for exploring the energy-latency tradeoffs of the communication activities.
39238334
Information Processing and Routing in Wireless Sensor Networks
Introduction of Wireless Sensor Networks Background Energy Models Information Processing within a Collocated Cluster Information Transportation over a Tree Substrate Information Routing with Tunable Compression.
2701730
Data Gathering with Tunable Compression in Sensor Networks
We study the problem of constructing a data gathering tree over a wireless sensor network in order to minimize the total energy for compressing and transporting information from a set of source nodes to the sink. This problem is crucial for advanced computationally intensive applications, where traditional "maximum" in-network compression may result in significant computation energy. We investigate a tunable data compression technique that enables effective trade-offs between the computation and communication costs. We derive the optimal compression strategy for a given data gathering tree and then investigate the performance of different tree structures for networks deployed on a grid topology, as well as general graphs. Our analytical results pertaining to the grid topology and simulation results pertaining to the general graphs indicate that the performance of a simple greedy approximation to the Minimal Steiner Tree (MST) provides a constant-factor approximation for the grid topology and good average performance on the general graphs. Although, theoretically, a more complicated randomized algorithm offers a polylogarithmic performance bound, the simple greedy approximation of MST is attractive for practical implementation.
16908353
The Dynamic Grey Radial Basis Function Prediction Model and its Applications
The dynamic gray radial basis function (DGRBF) prediction model is the improvement of traditional dynamic grey prediction model GM (1,1). It gives the dynamic algorithm of acquiring optimized initial conditions and identifying parameters like metabolism, and then the model combines the characters of RBF neural networks, and therefore has the ability of dynamic prediction on small volume of samples. The DGRBF prediction model has been applied in the practical engineering successfully, and the experiment results demonstrate that model and its intelligent optimizing algorithm are capable of predicting in a long term and the desired data could be acquired accurately, easily and conveniently
2706190
Shedding New Light on Sequence Design Criteria for Multipath Channels
The merit factor (MF) introduced by Golay has long been accepted as the standard criterion to evaluate and design binary sequences with good anti-multipath property in sonar, radar, and communication systems for its theoretical tightness and practical simplicity. In this paper, we first show that the MF is a biased anti-multipath performance evaluation metric in theory and, more importantly, is not a pertinent sequence design criterion in practice for most binary sequences of practical interest. Then we propose the weighted merit factor (WMF) based on a non-uniform weighting of the out-of-phase aperiodic autocorrelation function (ACF) that provides accurate measurement of self-generated interference for the constant amplitude complex-valued sequences and the nonconstant modulus ones. Based on the WMF, a list of "bad" (of low MFs) binary sequences (lengths 33-95) with better anti-multipath performance than the "best" (known) ones have been designed to verify its greater pertinence over the MF as a sequence design criterion for sonar, radar, and communication systems. Moreover, we extend the weighted correlation model of the WMF to the code-division multiple-access (CDMA) systems and propose the weighted cross-correlation factor (WCF) to evaluate the sequence set's multiple-access interference (MAI) rejection property in the context of multipath propagation. Theoretical analysis corroborated by simulations confirms that the WCF provides greater practical pertinence and analytical tractability over the current standard criterion.
18554601
Fault-tolerant routing algorithm for RDT structure
RDT (recursive diagonal torus) is a class of interconnection networks for massively parallel computers (MPCs). It consists of recursively structured mesh/torus connections. It has been proved that RDT supports better performances than most direct networks. SINOMP designed for the structure simulation and performance analysis between RDT and those networks is proposed. The simulation results also prove the good performances of RDT. In this paper, the fault-tolerant routing algorithms on the RDT structure are proposed and discussed. They select one of the shortest routes computed with the routing vector on the non-faulty network by using the different rank order. The additional hops are used to send packet only when all the shortest routes have faulty links/nodes. The proposed algorithms need no additional virtual channels for fault tolerant and support a reasonably large number of faults without significantly degrading the system performance.
17384103
RDT Properties and Evaluations
Proposed for MPCs, RDT has already been proved to support better performances than most of the direct network, such as smaller diameter based on its vector routing algorithm, smaller degree, embedded mesh/torus topology, etc. It gives a network form method to form groups of networks with recursively structured torus/torus-like networks. A RDT structure can be formed with the method and its related parameters. After analyzing its performance by the average distance, the descending vector routing reducing redundant computations and the fault-tolerant routing algorithm are proposed. A simpler structure named RDT(2,2,1)/a are proposed for the parallel systems with no more than 5000 nodes and given its performance evaluation. Considering the structure features of the practical RDTs, they are suitable for the interconnection network of an NoC design. The design of laying out RDT(2,2, 1)/a is proposed and proved to be available
14448098
Research on Dynamic Task Assignment in Grid Workflow System
Task assignment in grid workflow system should be designed to adapt well with the grid which allow people from different organizations to work together in the same workflow process. To ensure grid workflow systems could assign the task to the most suitable person, a novel solution is proposed firstly. Then two description languages GHRSL and HRRL are defined. GHRSL (grid human resource specification language) describes people as grid resources. HRRL (human resources requirement language) describes human resources requirement of workflow tasks. Finally, the evaluation method and the algorithm of dynamic task assignment are also proposed. Based on these, the grid workflow system could assign tasks dynamically to the correct person(s)