Mobile Sampling of Sensor Field Data Using Controlled Broadcast

Li, Juzheng; Shatz, Sol M.; Kshemkalyani, Ajay D.

doi:10.1109/tmc.2010.233

Cited by 18 publications

(9 citation statements)

References 29 publications

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“…Two variants of such approach are available. In first, the network topology is designed in such a way that the network can tolerate failures without degrading its performance in terms of coverage and connectivity [14][15][16][17]. In the second variant, some sensor nodes are augmented in network topology strategically [18][19] for tolerating from failures.…”

Section: Related Workmentioning

confidence: 99%

CPFR: Coverage preserving failure recovery in wireless sensor networks

Sharma

2015

2015 International Conference on Advances in Computer Engineering and Applications

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Since sensor nodes in wireless sensor networks (WSNs) are deployed randomly in hostile and ill-disposed environments, failures occur more frequently and unexpectedly as compared to other traditional networks. These frequent faults and failures in the network are major attributes towards poor quality of services (QoS). Therefore, for providing better QoS, such failures should be identified and recovered timely. On the other hand, wireless sensor nodes are resource constrained battery operated devices. Therefore, the failure diagnosis and recovery procedure should be energy efficient. In this work, we propose an energy efficient mechanism to diagnose and recover failures. At first, we propose a very low false alarming rate consensus based failure identification mechanism for diagnosing failures in the network. Secondly, an energy efficient coverage preserving failure recovery (CPFR) mechanism is proposed for recovering failures and maintaining an adequate coverage. The ns-2 based result shows that proposed scheme is able to diagnose failures with very low false alarming rate and is also able to recover failures by maintaining coverage above a threshold.

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Section: Related Workmentioning

confidence: 99%

CPFR: Coverage preserving failure recovery in wireless sensor networks

Sharma

2015

2015 International Conference on Advances in Computer Engineering and Applications

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“…In [10] "Band-based Directional transmits" an algorithmic method, has been commenced to organize the course of transmits that starts by sensor nodes. The objective would be to communicate every single transmit regarding sensor files to the removable destroy, so dipping pricey upon warding regarding sensor files packets.…”

Section: B Mobilitymentioning

confidence: 99%

“…An algorithm is planned by the author Juzheng Li, et. al., [10] to avoid the sinkhole problem. Sensors are statically organized into precise bands with familiar evolution ranges to accomplish uniform energy.…”

Section: Fig2 a 4-band Configurationmentioning

confidence: 99%

“…Given a precise sampling job, the author Juzheng Li, et. al., [10] separates the complete sampling section into numerous concentric circles as shown in " Fig.2", with the break among circles significant bands. The Band-based Directional Broadcast system can hold the cell object as the descend.…”

Section: Fig2 a 4-band Configurationmentioning

confidence: 99%

“….,[10] presented Mobile Sampling involving Sensor Discipline Data Employing Managed Transmit, Shourui Tian et. al., [27] Querying Sensor Communities Employing Ad-hoc Mobile phones: A Binary Layer Networking Approach, Scott C.-H. Huang et.…”

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confidence: 99%

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Performance analysis of mobile sampling and broadcast scheduling in wireless sensor networks

Rajasekar¹,

Periasamy²

2013

2013 International Conference on Current Trends in Engineering and Technology (ICCTET)

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The concept of using mobile objects to gather samples from a sensor field has been not long ago proposed. Mobile objects can be used to collect models from a sensor field. Inhabitant cars and even humans geared up along with appropriate instant connection units may be used because cell basins that will reclaim sensor-data by various factors within a huge sensor subject. An essential will be the way to set up your sensor data in a fashion that will be electricity adept intended for your sensor nodes. The path of sending the sensor data is efficiently identified but consumes more cost to forward sensor data packet. Various techniques have discussed the mobile sampling and broadcast scheduling procedure for expressing a sensor node proficiently to a preferred data at a given point of time period. In this paper, the performance of the mobile sampling and broadcasting scheduling in sensor network on the basis of transmission speed, Query result precision and Deliverability is analyzed.

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SGDD: self‐managed grid‐based data dissemination protocol for mobile sink in wireless sensor network

Majma

Almassi

Shokrzadeh

2015

Int J Communication

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SUMMARYThe reduction of energy consumption in order to increase network lifetime is one of the most major challenges in the design of wireless sensor networks. During data dissemination, the sensors that are located in the sink's neighborhood are responsible to relay data to the other nodes; hence, their energy is exhausted expeditiously. Therefore, the idea of utilizing mobile sinks can be so advantageous to decrease energy consumption during data dissemination process. In this paper, we propose self-managed grid-based data disseminating protocol for mobile sink in wireless sensor networks by using the idea of constructing a virtual grid. In self-managed grid-based data disseminating protocol, sink and nodes map their geographical position to a virtual location. In order to increase the performance, we have employed a cell head for each grid cell. Cell heads are selected based on two parameters, centralization and residual energy. Our data dissemination protocol is simple and has low overhead to construct and maintain. Also, we have presented a new method for sink location update, which leads to the least cost in data transfer. Simulation results illustrate that by utilizing hierarchical functionality and determining an optimal size for grid cells, energy consumption is decreased, which leads to increasing network lifetime.

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Mobile Sampling of Sensor Field Data Using Controlled Broadcast

Cited by 18 publications

References 29 publications

CPFR: Coverage preserving failure recovery in wireless sensor networks

CPFR: Coverage preserving failure recovery in wireless sensor networks

Performance analysis of mobile sampling and broadcast scheduling in wireless sensor networks

SGDD: self‐managed grid‐based data dissemination protocol for mobile sink in wireless sensor network

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