## 2 Related Work
### Cross Layering Optimization  
Cross layer design breaks away from traditional network design, where each layer of the protocol stack operates independently and exchanges information with adjacent layers only. In the cross layer approach, information is exchanged between non-adjacent layers of the protocol stack in order to optimize decisions and better adapt to the environment. Examples of cross-layering architectures are described in [50, 51, 52, 53, 54].  
In [55], using a cross layer approach, authors study the tradeoff between network lifetime maximization and rate allocation problem by formulating these two problems as a constrained maximization problem. Using Lagrange dual decomposition, the original problem is vertically decomposed into three subproblems: (1) a rate control problem at the transport layer, (2) a contention resolution problem at the MAC Layer, and (3) a cross-layer energy conservation problem. Two fully distributed algorithms are derived for the first two subproblems. For the third subproblem, they first directly derive a partially distributed algorithm, and then propose a fully distributed approximation algorithm using network utility maximization framework. [PERSON] _et al_. [56, 57] characterized the tradeoff between maximizing the application performance and lifetime by considering a cross-layer design problem in a wireless sensor network with orthogonal link transmissions, which jointly maximized the network utility and lifetime. The idea is to compute an optimal set of source rates, network flows, and radio resources at the transport, network, and radio resource layers respectively, while jointly maximizingthe network utility and lifetime. They show that the cross-layer optimization problem decomposes both horizontally (across nodes) and vertically (across different layers in the protocol stack) into simpler subproblems allowing a fully distributed solution. In [58], authors investigate the problem of the lifetime maximization in a wireless sensor network under the constraint of the end-to-end transmission success probability. A cross-layering strategy that considers physical layer (_i.e._, power control), MAC layer (_i.e._, retransmission control) and network layer (_i.e._, routing protocol) jointly is adopted. They first present a near-optimal retry limit allocation algorithm for a given routing path. This allocation determines per-hop success probability for each link along the path in order to minimize the total energy consumption while guaranteeing the reliability constraint. Then, an optimal routing and power control algorithm that maximizes the network lifetime is developed. Simulation results reveal that a trade-off relation exists between the network lifetime maximization and the reliability constraint, and that the network lifetime can be increased significantly by employing the proposed algorithms.  
In this paper, we show in Section 3.3 how to optimize the EOLSR routing protocol, taking advantage of information provided by (i) the MAC layer (e.g. the received power to use only links of good quality), and the application layer (e.g., existence of a sink node). Similarly, we optimize SERENA in Section 4.4 taking advantage of cross-layering to reduce the end-to-end delays in data gathering applications.