在隨建即連行動網路(MANET)中，如何節省裝置(device)能源是值得探討的一項重要議題。在相關的研究，如GAF利用區域切割的方式，將節點切割出許多不同的區域出來，再利用位於相同一個區域的眾多節點中，只需要一個節點是醒著(coordinator)來幫忙做轉傳資料的動作，而此時其它在同一區域的節點則可以睡覺的特性，來達到節省能源的目地。
這樣的方法確實節省了大量的能源，但仍有些許改善的空間。第一個希望改善的是，位於所有同一區域內部的眾多節點，我們希望剩餘能量較多的節點可以減少睡眠時間，如此的話，剩餘能量多的節點會有比較大的機會可以去競爭當協調者(coordinator)。同樣地，剩餘能量較少的節點，我們希望可以增加睡眠時間，可以減少浪費能量在競爭上面及需要花能量在維持醒著狀態。如果每一個協調者(coordinator)都按照此準則選出來，則整個網路的存活時間就會拉長。
第二是區域跟區域之間能夠平衡彼此的平均剩餘能量。我們希望的是，若有一個區域目前的平均剩餘能量，其中當然也包含自己所在的區域的全部平均剩餘能量，如果大於所有自己所在的各個相鄰區域的平均剩餘能量，目前在這區域內的協調者(coordinator)可以把剛醒過來的節點分派去支援其它周圍平均剩餘能量最小的區域，來幫忙做轉傳資料及處理管理封包的事。如果區域跟區域之間可以按照此準則進行的話，則有助於整個網路的存活時間。
第三是我們希望隨建即連行動網路(MANET)在建立繞送路徑時，也可以按照時間跟剩餘能量的比例方式來選出此路徑上的各個節點。
我們並分析出EPR演算法在平衡協調者之間的資料傳輸量上面，可以有效的延長網路的存活時間，並將EPR演算法的概念套用到我們的方法上面。其中我們所提繞送路徑的方法，在針對延長網路存活時間的議題上面，仍然有再待改進。
以上三個改善的方法目的就是希望資料或管理封包都是剩餘能量較大的節點來做轉傳資料或處理管理封包的動作，進而達成平衡區域內及區域之間能源的使用率，最終並因此得以延長整體隨建即連行動網路(MANET)的生命週期(lifetime)。

In the field of mobile ad-hoc networks, energy-awareness schemes are more complex and important. How to save the energy of devices is an important topic that is worth probing into. In relevant research, for instance, the way of GAF divides the simulation area in a lot of square grids. There are so many nodes but only a coordinator needs to wake up in the same grid. Coordinator helps other nodes transfer or handle the management packets so that other nodes can sleep in the same grid. Such this method saves a lot of energy.
GAF has really saved a large amount of energy, but there is still something we can improve. First is when the all nodes are inside the same grid, we hope that the nodes which have more residual energy can reduce its sleep time. Therefore they have a bigger chance to compete and be a coordinator. Similarly, we hope that the nodes which have less residual energy nodes can increase its sleep time. Therefore they can save energy because they avoid wasting energy on competition and keeping nodes hold on idle state. According this way, network lifetime is extended.
The second is we want to balance the average residual energy between grid and grid. If there is an average residual energy of all neighbor grids including myself grid and is greater than the average residual energy of all each neighbor grids. Coordinator assigns a node which just wakes up to the smallest average residual energy of a neighbor grid. Therefore the node can help the neighbor grid transfer data packets and handle management packets. If GAF can follow this way, network lifetime is extended in most cases.
The third is we hope when AODV sets up a routing path in mobile ad hoc network with GAF, it can also choose the coordinator by the ratio between timer interval and residual energy of all coordinators to set up a reverse path.
We have studied in EPR and find out that EPR can extend network lifetime efficiently according to balance the forwarding data between coordinators. Therefore, we adopt the concept of EPR and implement it into our algorithm. The modified method of the path routing we have talked above, it is still a lot of work to do about the issue of extending the network lifetime.
The goals we briefly described above are that the nodes which have more residual energy have more chances to be a coordinator. The nodes which have less residual energy sleep more time and have less chance to be a coordinator as well. Such methods balance the average residual energy inside grid and among grids, and eventually the lifetime of whole mobile ad-hoc network is extended.

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