QoS-BASED ROUTING PROTOCOLS FOR WSNs in .NET framework

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QoS-BASED ROUTING PROTOCOLS FOR WSNs
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In SAR, a table-driven multipath approach is used to improve energy ef ciency in a low-mobility sensor network. The failure protection is addressed by having at least k-paths that have no common branches between a node and a sink. This is called a k-disjoint structure. However, the disjoint property creates strong coupling between routing tables, rendering localized recovery schemes ineffective. To reduce this effect, the disjoint requirement is relaxed outside the 1-hop neighborhood of the sink. Furthermore, localized path restoration procedures are used to decrease energy cost in failure recovery. Multiple paths from each node to a sink are created by building multiple trees, each rooted at the 1-hop neighborhood of the sink. Each node uses two parameters to create routing paths: r Energy resource that is estimated by maximum number of packets that can be routed without energy depletion, assuming that the node has exclusive use of the path. r Additive QoS metrics where higher metric implies lower QoS. Path selection is made by nodes that generate packets if no topology change occurs while packets are being routed to their destinations. The energy cost and delay of links are considered as additive QoS metrics. Packet priorities are used in a way that packets with higher priorities use paths with lower latency. In short, for each packet, a weighted QoS metric is computed as the product of a weight coef cient (the priority of the packet) and the additive QoS metric. Hence, QoS is provided to each packet relative to its priority level, where higher QoS is given to higher-priority level packets. The SAR algorithm minimizes the average QoS metric throughout the lifetime of the network. Periodic metric updates triggered at the sink node are used to account for possible changes in the QoS on individual paths and the changes in energy resources. Simulations show that SAR performs better than a minimum metric algorithm that lowers energy consumption without considering packet priorities. Furthermore, failure recovery is handled by local handshakes between upstream and downstream neighbors in paths. SAR algorithm addresses low-mobility networks, and routes are established at packet sources considering link costs and energy resources as a QoS parameter. Packet priorities are taken into account to relay high-priority packets to popular paths in terms of latency. However, the scheme requires resource-related topology information at packet sources that require frequent parameter updates by a common sink. This incurs high overhead in WSNs with moderate or high mobility and in WSNs carrying high data rates. 13.4.2 Energy-Aware Routing in Mobile and Wireless Ad Hoc Networks [18] Before focusing on energy-aware routing protocols for WSNs, it is worth focusing on energy-saving routing protocol design for wireless ad hoc networks. These solutions are also directly applicable to WSNs with limited number of nodes and where a number of potentially mobile, high-capability nodes need to communicate possibly
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QoS-BASED COMMUNICATION PROTOCOLS IN WIRELESS SENSOR NETWORKS
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over sensor nodes. A good example of modifying existing routing protocols to be energy-aware has been presented in reference [18]. In this paper, two reactive ad hoc routing protocols, namely DSR [19] and TORA [20], are modi ed to deliver QoS by introducing energy-awareness. DSR and TORA protocols involve a route discovery phase initiated when a mobile source node needs to send data packets to the destination node but does not have an active and valid route to it. Route discovery is performed using the control packets called route request packets (RREQ). The source node broadcasts RREQs and waits for a control packet called the route reply packet (RREP). Using the received RREP, the source node updates its routing table, which is used to keep track of active routes to individual destination nodes in the network. Intermediate nodes, which forward RREQ and RREP packets between source and destination nodes, also use RREP packets to update their routing tables. Although these protocols are effective and robust, the broadcast of RREQ packets leads to unnecessary packet transmissions and inef cient use of limited energy resources. In reference [18], two modi ed protocols, EDSR and ETORA, based on the existing DSR and TORA protocols, are introduced, respectively. Both EDSR and ETORA involve an additional RREQ forwarding mechanism that does not exist in DSR and TORA. In an intermediate node, this mechanism considers the current energy level of the node, the energy level of the previous sender node, and the distance to the source node when making routing decisions. Distance estimation is accomplished using time stamps in RREQ packets. When a node transmits an RREQ packet, it records the time of transmission in the RREQ. Intermediate nodes that receive this RREQ calculate the time difference between transmission and the reception time of the RREQ to estimate their distances to the sender node. Besides transmission times, energy levels of the nodes right before RREQ transmission are also recorded in RREQs. The RREQ forwarding decision in reference [18] is based on cutoff circles that are placed around each node in a network. Upon the reception of an RREQ packet, an intermediate node calculates the diameter of its cutoff circle using its energy level, the energy level of the previous node sending this RREQ packet, and its distance to the previous node calculated by the time stamp in the RREQ packet. The receiving node simply drops the packet, hence does not forward it, if its cutoff circle encircles the previous node. In reference [18], ETORA and EDSR are shown to outperform TORA and DSR, respectively, in terms of overall network throughput, the average number of data packets received at destinations, average data transmission delay, and energy consumption. The pseudocode of the proposed RREQ forwarding algorithm is given in Figure 13.4. 13.4.3 Energy-Aware QoS Routing Protocol for WSNs [21] The information delivery in video sensor networks requires end-to-end delay guarantees. The QoS-based routing protocol proposed in reference [21] aims to sustain paths that can guarantee such delays for real-time traf c while supporting non-real-time (best-effort) data ows, as well. The network architecture assumed in this proposal
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