A critical aspect of applications with wireless sensor networks is network lifetime. Power-constrained wireless sensor networks are usable as long as they can communicate sensed data to a processing node. Sensing and communications consume energy, therefore judicious power management and sensor scheduling can effectively extend network lifetime. To cover a set of targets with known locations when ground access in the remote area is prohibited, one solution is to deploy the sensors remotely, from an aircraft. The lack of precise sensor placement is compensated by a large sensor population deployed in the drop zone, that would improve the probability of target coverage. The data collected from the sensors is sent to a central node (e.g. cluster head) for processing. In this paper we propose un efficient method to extend the sensor network life time by organizing the sensors into a maximal number of set covers that are activated successively. Only the sensors from the current active set are responsible for monitoring all targets and for transmitting the collected data, while all other nodes are in a low-energy sleep mode. By allowing sensors to participate in multiple sets, our problem formulation increases the network lifetime compared with related work [M. Cardei et al], that has the additional requirements of sensor sets being disjoint and operating equal time intervals. In this paper we model the solution as the maximum set covers problem and design two heuristics that efficiently compute the sets, using linear programming and a greedy approach. Simulation results are presented to verify our approaches.

/pdf/energy-efficient-target-coverage-in-wireless-sensor-networks-2snkcx2hjq.pdf

Energy-efficient target coverage in wireless sensor networks

A survey of shape analysis techniques

Extracting a license plate is an important stage in automatic vehicle identification. It is very difficult because vehicle images are usually degraded and processing the images is computationally intensive. We propose a new method to extract the plate region using a distributed genetic algorithm. The algorithm offers robustness in dealing with deformation of vehicle images and inherent parallelism to improve the processing time. A test with seventy images shows an extraction rate of 92.8%, working well within real world situations. This results suggest that the proposed method is pertinent to be put into practical use.

A recognition of vehicle license plate using a genetic algorithm based segmentation

The paper presents work-in-progress on the cloud service provisioning across multiple cloud providers. The work assumes the emergence of Cloud Brokers between customers and cloud providers. The brokers split user requests and ensure provisioning from multiple providers. An exact splitting algorithm is developed to efficiently split the cloud requests among the multiple cloud platforms with the aim of decreasing the cost for customers. This splitting is formulated as a Mixed Integer Program and this is combined with Open Flow and NOX technologies that achieve flow based inter-cloud networking. A new controller module is developed and integrated in NOX to configure the Open Flow switches for inter-cloud path establishments.

Cloud Service Delivery across Multiple Cloud Platforms

Construction of 3D solid objects from orthographic views

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