5,734 research outputs found
Priority based Congestion Control Mechanism in Multipath Wireless Sensor Network
Wireless Sensor Network (WSN) is a network composed of distributed autonomous devices using sensors. Sensor nodes send their collected data to a determined node called Sink. The sink processes data and performs appropriate actions. Nodes using routing protocol determine a path for sending data to sink. Congestion occurs when too many sources are sending too much of data for network to handle. Congestion in a wireless sensor network can cause missing packets, long delay, overall channel quality to degrade, leads to buffer drops. Congestion control mechanism has three phases, namely congestion detection, congestion notification and congestion control. In this paper is propose two bit binary notification flag to notify the congested network status for implicit congestion detection. For congested network status, we propose a priority based rate adjustment technique for controlling congestion in link level. Congested packet will be distributed equally to the child node to avoid packet loss and transition delays based on technique. Furthermore, this technique allocates the priority of many applications simultaneously running on the sensor nodes, which route is own data as well as the data generated from other sensor nodes. The results show that the proposed technique achieves better normalized throughput and total scheduling rate with the avoiding packet loss and delay
Efficient Aggregation of Multiple Classes of Information in Wireless Sensor Networks
Congestion in a Wireless Sensor Network (WSN) can lead to buffer overflow, resource waste and delay or loss of critical information from the sensors. In this paper, we propose the Priority-based Coverage-aware Congestion Control (PCC) algorithm which is distributed, priority-distinct, and fair. PCC provides higher priority to packets with event information in which the sink is more interested. PCC employs a queue scheduler that can selectively drop any packet in the queue. PCC gives fair chance to all sensors to send packets to the sink, irrespective of their specific locations, and therefore enhances the coverage fidelity of the WSN. Based on a detailed simulation analysis, we show that PCC can efficiently relieve congestion and significantly improve the system performance based on multiple metrics such as event throughput and coverage fidelity. We generalize PCC to address data collection in a WSN in which the sensor nodes have multiple sensing devices and can generate multiple types of information. We propose a Pricing System that can under congestion effectively collect different types of data generated by the sensor nodes according to values that are placed on different information by the sink. Simulation analysis show that our Pricing System can achieve higher event throughput for packets with higher priority and achieve fairness among different categories. Moreover, given a fixed system capacity, our proposed Pricing System can collect more information of the type valued by the sink
Traffic Management in Wireless Sensor Network Based on Modified Neural Networks
Wireless Sensor Networks (WSNs) are event-driven network systems consist of many sensors node which aredensely deployed and wirelessly interconnected that allow retrieving of monitoring data. In Wireless sensor network,whenever an event is detected, the data related to the event need to be sent to the sink node (data collection node). Sink nodeis the bottleneck of network there may be chance for congestion due to heavy data traffic. Due to congestion, it leads to dataloss; it may be important data also. To achieve this objective, soft computing based on Neural Networks (NNs) CongestionController approach is proposed. The NN is activated using wavelet activation function that is used to control the traffic ofthe WSN. The proposed approach which is called as Modified Neural Network Wavelet Congestion Control (MNNWCC), hasthree main activities: the first one is detecting the congestion as congestion level indications; the second one is estimated thetraffic rate that the upstream traffic rate is adjusted to avoid congestion in next time, the last activates of the proposedapproach is improved the Quality of Services (QoS), by enhancement the Packet Loss Ratio (PLR), Throughput (TP), BufferUtilization (BU) and Network Energy (NE) . The simulation results show that the proposed approach can avoid the networkcongestion and improve the QoS of network
JiTS: Just-in-Time Scheduling for Real-Time Sensor Data Dissemination
We consider the problem of real-time data dissemination in wireless sensor
networks, in which data are associated with deadlines and it is desired for
data to reach the sink(s) by their deadlines. To this end, existing real-time
data dissemination work have developed packet scheduling schemes that
prioritize packets according to their deadlines. In this paper, we first
demonstrate that not only the scheduling discipline but also the routing
protocol has a significant impact on the success of real-time sensor data
dissemination. We show that the shortest path routing using the minimum number
of hops leads to considerably better performance than Geographical Forwarding,
which has often been used in existing real-time data dissemination work. We
also observe that packet prioritization by itself is not enough for real-time
data dissemination, since many high priority packets may simultaneously contend
for network resources, deteriorating the network performance. Instead,
real-time packets could be judiciously delayed to avoid severe contention as
long as their deadlines can be met. Based on this observation, we propose a
Just-in-Time Scheduling (JiTS) algorithm for scheduling data transmissions to
alleviate the shortcomings of the existing solutions. We explore several
policies for non-uniformly delaying data at different intermediate nodes to
account for the higher expected contention as the packet gets closer to the
sink(s). By an extensive simulation study, we demonstrate that JiTS can
significantly improve the deadline miss ratio and packet drop ratio compared to
existing approaches in various situations. Notably, JiTS improves the
performance requiring neither lower layer support nor synchronization among the
sensor nodes
Selecting source image sensor nodes based on 2-hop information to improve image transmissions to mobile robot sinks in search \& rescue operations
We consider Robot-assisted Search Rescue operations enhanced with some
fixed image sensor nodes capable of capturing and sending visual information to
a robot sink. In order to increase the performance of image transfer from image
sensor nodes to the robot sinks we propose a 2-hop neighborhood
information-based cover set selection to determine the most relevant image
sensor nodes to activate. Then, in order to be consistent with our proposed
approach, a multi-path extension of Greedy Perimeter Stateless Routing (called
T-GPSR) wherein routing decisions are also based on 2-hop neighborhood
information is proposed. Simulation results show that our proposal reduces
packet losses, enabling fast packet delivery and higher visual quality of
received images at the robot sink
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