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Furthermore, these additional mechanisms must be local and should not alter the overall tree structure 1349 QoS for Data Relaying in Hierarchical WSNs [27] This study presented in reference [27] addresses the selection of one or more routes from sensors to a base station The routes are chosen such as to satisfy the delay requirements In this study, large heterogeneous WSNs are considered which are organized in three tiers of hierarchy: a base station (BS), relay nodes (RN), and nally sensor nodes acting as data sources Relay nodes are placed such that connectivity is maintained Additional relay nodes are placed to improve energy consumption and reduce interference However, increasing the number of relay nodes increases the end-to-end delay Furthermore, relay nodes that are closer to the base station consume more energy compared to others.

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q = (qx ,q y ) v = (vx ,vy) d(u,q)

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To address these issues, a hybrid approach is proposed that introduces relay gateways (RG) that receive data from relay nodes and send them directly (in a single hop) to the base station RGs are pre-deployed in the network and are stationary The routing decisions at RN-RG and RN-RN communication level consider the system lifetime as a constraint System lifetime is de ned as the time until at least one RN or RG depletes its energy supply The lifetime of a node is modeled by the maximum amount of traf c it can handle, which is called the node capacity The routing from sensors to relay nodes is assumed to be handled by low level protocols Hence, this protocol only deals with ef cient routing of data among relay nodes by delivering it to one of the RGs while meeting the delay requirements.

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Two different cases of selecting a relay path are proposed: multipath relaying with delay constraints (MPD) and unconstrained multipath relaying (MP) Two different algorithms that are both centralized and optimal are proposed to solve these problems In the MP problem, the aim is to minimize the end-to-end communication cost while meeting the capacity constraints of RNs and RGs However, this problem does not deal with end-to-end delays The WSN is modeled as a directed graph composed of a set of vertices (composed of RNs and RGs) and a set of arcs which represent the edges between vertices The cost c of sending a packet over an arc is de ned as a function of individual arcs Furthermore, the ow of data over an arc is de ned as a separate function x, which is used to model the routing decisions of every RN..

v v p = (d(u,p), 0)

Hence the total cost of communication over the selected arcs from source RN to RG, x(a)c(a), is minimized, where a is an arc The capacity of a node i is represented as (i), whereas the total amount of data forwarded to a relay from sensors is (i), which is called the demand of i The set of all arcs entering a node i is (i ), and the set of all arcs leaving i is (i+) The minimization of total cost is subject to x( (i+)) x( (i )) = (i), meaning that the demand of a relay node i is equal to the net ow into i, that is, x( (i )) t (i) (i), where it is assumed that transmission requires t/(1 t) more energy than reception The MP problem is modeled as a transshipment problem, which is a classical problem in operations research.

u = (0,0)

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