10511055
RF2ID: A Reliable Middleware Framework for RFID Deployment
The reliability of RFID systems depends on a number of factors including: RF interference, deployment environment, configuration of the readers, and placement of readers and tags. While RFID technology is improving rapidly, a reliable deployment of this technology is still a significant challenge impeding widespread adoption. This paper investigates system software solutions for achieving a highly reliable deployment that mitigates inherent unreliability in RFID technology. We have developed (1) a virtual reader abstraction to improve the potentially error-prone nature of reader generated data (2) a novel path abstraction to capture the logical flow of information among virtual readers. We have designed and implemented an RFID middleware: RF2ID (reliable framework for radio frequency identification) to organize and support queries over data streams in an efficient manner. Prototype implementation using both RFID readers and simulated readers using an empirical model of RFID readers show that RF2ID is able to provide high reliability and support path-based object detection.
6817196
Design of Adaptive Overlays for Multi-scale Communication in Sensor Networks
In wireless sensor networks, energy and communication bandwidth are precious resources. Traditionally, layering has been used as a design principle for network stacks; hence routing protocols assume no knowledge of the application behavior in the sensor node. In resource-constrained sensor-nodes, there is simultaneously a need and an opportunity to optimize the protocol to match the application. In this paper, we design a network architecture that efficiently supports multi-scale communication and collaboration among sensors. The architecture complements the previously proposed Abstract Regions architecture for local communication and collaboration. We design a self-organizing hierarchical overlay that scales to a large number of sensors and enables multi-resolution collaboration. We design effective Network Programming Interfaces to simplify the development of applications on top of the architecture; these interfaces are efficiently implemented in the network layer. The overlay hierarchy can adapt to match the collaboration requirements of the application and data both temporally and spatially. We present an initial evaluation of our design under simulation to show that it leads to reduced communication overhead, thereby saving energy. We are currently building our architecture in the TinyOS environment to demonstrate its effectiveness.
1898402
DFuse: a framework for distributed data fusion
Simple in-network data aggregation (or fusion) techniques for sensor networks have been the focus of several recent research efforts, but they are insufficient to support advanced fusion applications. We extend these techniques to future sensor networks and ask two related questions: (a) what is the appropriate set of data fusion techniques, and (b) how do we dynamically assign aggregation roles to the nodes of a sensor network. We have developed an architectural framework, DFuse, for answering these two questions. It consists of a data fusion API and a distributed algorithm for energy-aware role assignment. The fusion API enables an application to be specified as a coarse-grained dataflow graph, and eases application development and deployment. The role assignment algorithm maps the graph onto the network, and optimally adapts the mapping at run-time using role migration. Experiments on an iPAQ farm show that, the fusion API has low-overhead, and the role assignment algorithm with role migration significantly increases the network lifetime compared to any static assignment.
254985
Multicriteria Network Design Using Evolutionary Algorithm
In this paper, we revisit a general class of multicriteria multi-constrained network design problems and attempt to solve, in a novel way, with Evolutionary Algorithms (EAs). A major challenge to solving such problems is to capture possibly all the (representative) equivalent and diverse solutions. In this work, we formulate, without loss of generality, a bi-criteria bi- constrained communication network topological design problem. Two of the primary objectives to be optimized are network delay and cost subject to satisfaction of reliability and flowconstraints. This is a NP-hard problem so we use a hybrid approach (for initialization of the population) along with EA. Furthermore, the twoobjective optimal solution front is not known a priori. Therefore, we use a multiobjective EA which produces diverse solution space and monitors convergence; the EA has been demonstrated to work effectively across complex problems of unknown nature. We tested this approach for designing networks of different sizes and found that the approach scales well with larger networks. Results thus obtained are compared with those obtained by two traditional approaches namely, the exhaustive search and branch exchange heuristics.
2138355
Specification of secure distributed collaboration systems
The focus of this paper is on a specification model for defining security and coordination policies for distributed collaboration and workflow systems. This work is motivated by the objective to build distributed collaboration systems from their high level specifications. We identify here unique requirements for secure collaboration, specifically role admission and activation constraints, separation of duties, dynamic access control, and a model for multiuser participation in a role. We present a role-based model for specifying coordination and dynamic security requirements in collaboration systems. It also supports hierarchical structuring of a large collaboration environment using the concept of activities, which define a naming scope and a protection domain to specify security and coordination policies. We have implemented this specification model in XML and used it to construct the runtime environments for distributed collaboration systems using a policy based middleware.
2162080
Harbor: software-based memory protection for sensor nodes
Many sensor nodes contain resource constrained microcontrollers where user level applications, operating system components, and device drivers share a single address space with no form of hardware memory protection. Programming errors in one application can easily corrupt the state of the operating system or other applications. In this paper, we propose Harbor, a memory protection system that prevents many forms of memory corruption. We use software based fault isolation ("sandboxing") to restrict application memory accesses and control flow to protection domains within the address space. A flexible and efficient memory map data structure records ownership and layout information for memory regions; writes are validated using the memory map. Control flow integrity is preserved by maintaining a safe stack that stores return addresses in a protected memory region. Run-time checks validate computed control flow instructions. Cross domain calls perform low-overhead control transfers between domains. Checks are introduced by rewriting an application's compiled binary. The sand-boxed result is verified on the sensor node before it is admitted for execution. Harbor's fault isolation properties depend only on the correctness of this verifier and the Harbor runtime. We have implemented and tested Harbor on the SOS operating system. Harbor detected and prevented memory corruption caused by programming errors in application modules that had been in use for several months. Harbor's overhead, though high, is less than that of application-specific virtual machines, and reasonable for typical sensor workloads.
16795084
Analysis of a Multiobjective Evolutionary Algorithm on the 0-1 knapsack problem
Multiobjective Evolutionary Algorithms (MOEAs) are increasingly being used for effectively solving many real-world problems, and many empirical results are available. However, theoretical analysis is limited to a few simple toy functions. In this work, we select the well-known knapsack problem for the analysis. The multiobjective knapsack problem in its general form is NP-complete. Moreover, the size of the set of Pareto-optimal solutions can grow exponentially with the number of items in the knapsack. Thus, we formalize a (1 + e)-approximate set of the knapsack problem and attempt to present a rigorous running time analysis of a MOEA to obtain the formalized set. The algorithm used in the paper is based on a restricted mating pool with a separate archive to store the remaining population; we call the algorithm a Restricted Evolutionary Multiobjective Optimizer (REMO). We also analyze the running time of REMO on a special bi-objective linear function, known as LOTZ (Leading Ones : Trailing Zeros), whose Pareto set is shown to be a subset of the knapsack. An extension of the analysis to the Simple Evolutionary Multiobjective Optimizer (SEMO) is also presented. A strategy based on partitioning of the decision space into fitness layers is used for the analysis.
41727338
Multiobjective Genetic Search for Spanning Tree Problem
A major challenge to solving multiobjective optimization problems is to capture possibly all the (representative) equivalent and diverse solutions at convergence. In this paper, we attempt to solve the generic multi-objective spanning tree (MOST) problem using an evolutionary algorithm (EA). We consider, without loss of generality, edge-cost and tree-diameter as the two objectives, and use a multiobjective evolutionary algorithm (MOEA) that produces diverse solutions without needing a priori knowledge of the solution space. We test this approach for generating (near-) optimal spanning trees, and compare the solutions obtained from other conventional approaches.