Hi, this is another publication:"A Survey on Routing Protocols for Wireless Sensor Networks"

http://www.csee.umbc.edu/~younis/Publications/JAdHoc/SensNetRouting.pdf

This paper proposes an improvement of LECH and implementation is done on matlab.

http://fr.slideshare.net/divya_prabha/project-report-on-an-energy-efficient-routing-protocol-in-wireless-sensor-networks?qid=2b1b93ff-fbe1-4220-a665-0fedd4dc07e0&v=default&b=&from_search=2

Thank you for your response , I will check and read it , but I still need your help ( my friends) to accomplish my project  .

There is a plethora of routing protocols for maximizing the life time of WSN and one big problem is that there are very few works that actually compare with other proposals so it is very hard to determine which is the best and under what conditions. Another consideration is that the definition for what lifetime is varies a lot between proposals. Some consider when the last nodes die and some when a fraction of nodes remain. I have myself proposed a solution to keep the ENTIRE network alive as long as possible in case it is needed that all nodes live as long as possible. A nice side effect is that one can predict when this will happen with fairly good accuracy. You can check out the RETT protocol by Matrouk and Landfeldt if this is what you are after.

Article RETT-gen: A globally efficient routing protocol for wireless...

Understanding Wireless Routing For IoT Networks 

The routing of data from source to sink is an integral part of any large-scale wireless sensing and Internet of Things (IoT) solution. Unplugged and/or mobile embedded devices used in such low-powered and lossy network (LLN) applications are always severely constrained in terms of available power. Therefore, energy-efficient routing of data becomes critical to any long-term sustainable solution.

Fundamental Building Blocks Of RPL

At its core, RPL organizes its topology as a directed acyclic graph (DAG) that is partitioned into one or more destination oriented DAGs (DODAGs), with one DODAG per sink (see the figure). Each node in a DODAG, which is akin to a routing device in an IoT solution, has a node rank that defines the node’s position relative to other nodes with respect to a DODAG root.

The exact way RPL node rank is computed depends on the DAG’s objective function (OF). An OF defines how routing metrics, optimization objectives, and related functions are used to compute rank. In essence, the OF dictates the DODAG formation. The RPL topology is built using control messages that are transmitted as ICMPv6 messages. The three key RPL control messages are:

• DODAG information solicitation (DIS): The DIS solicits a DODAG information object (DIO) from an RPL node.

• DODAG information object (DIO): The DIO carries information that allows a node to discover a RPL Instance, learn its configuration parameters, select a DODAG parent set, and maintain the DODAG.

• Destination advertisement object (DAO): The DAO is used to propagate destination information upward along the DODAG.

To construct the DODAG topology, nodes may use a DIS message to solicit a DIO, or they may periodically send link-local multicast DIO messages. Nodes then listen for DIOs and use their information to join a new DODAG or to maintain an existing DODAG. Based on information in the DIOs, the node chooses parents that minimize the path cost to the DODAG root.

Conclusion

A successful implementation of the RPL could enable an IoT solution to meet its stated objective functions and goals. In the scope of RPL, a typical goal is to construct the DODAG according to a specific OF and to keep connectivity to a set of hosts. RPL is specifically optimized for MP2P and P2MP traffic patterns. Nodes are stateless, and the routing state information stored in each node is minimal. RPL also accounts for both link and node properties when choosing paths. And, link failures do not trigger a global network re-optimization.

For a large-scale IoT deployment (involving thousands of nodes and spread over a large geographical area), when the routing design and implementation minds the various features, functionalities, and attributes available in the RPL, the IoT solution could get a battery lifetime of years.3

The possibility of using IP-based networks could greatly reduce the energy and costs associated with wireless IoT communication, which would otherwise need expensive mobile-tower connectivity and GSM/EDGE-based communication. Such an RPL implementation could dramatically alter the rollout of IoT solutions for applications such as urban sensing networks.

And for increasing lifetime you must useing of X-MAC or other MAC protocols. For example some recently of these methods can be increase about 10 years.

 And about LEACH or different routing protocol, you should notice to these routing protocols are inefficient in 6LowPANs.

you can use the Ant Colony Algorithm(ACO) and Artificial Immune System(AIS).

AIS  is used for solving packet LOOP problem and to control route direction, while ACO algorithm is used for determining optimum route for sending the data packet, we infer that this will determine the optimum route from nodes towards base station so that energy exhaustion is balanced and lifetime is maximized.

LEACH also one of the important algorithms that consume less energy when it focuses to divide the nodes into clusters and allows only the cluster head transmit the data to base station , so it decreases the energy that leads to saving the network lifetime