\chapter{Conclusions and Future Work}

	\hsp{8mm} We conclude this thesis with a discussion of the
	relative advantages of our algorithm and some possible future work.

	{\bf Performance.} \ The simulation results show that our
	algorithm has a better performance. Both the delay and
	utilization are lower than that for the compared algorithm.
	When the message rate is very low and the groups are
	static, the compared algorithm might offer a slightly lower
	delay. But in that case, the delay is very low for both
	algorithms.

	{\bf Functionality.} \ This algorithm supports transmission
	from any node to any group, where the member of the group may
	be distributed across any number of groups, and may join and
	leave an group independently at any time.

	{\bf Scalability.} \ This algorithm is insensitive to the
	network topology, group size, and the number of groups.
	Whenever topology changes or a group birth or a group death
	occurs, or group membership changes, this algorithm executes
	exactly the same way.

	{\bf Compatibility.} \ Our algorithm is compatible with unicast
	environment. It does not require excessive information compared
	with that used in unicast environment. The routing tables of
	the neighboring nodes are usually available for many unicast
	algorithms such as the distributed Bellman-Ford algorithm
	mentioned in Chapter 2.

	{\bf Reliability.} \ This algorithm has the same probability of
	loss, or damage of packets as the unicast routing. Whenever the
	routing table changes, the radius $R$ is set to be $\infty$;
	this guarantees that no loss is caused by the routing table
	change.

	{\bf Simplicity.} \ This algorithm is conceptually simple and
	easy to implement; computation time complexity is only linear
	in group size, therefore it is very efficient. In addition, no
	delivery tree is to be maintained, so that no cost is incurred
	by maintaining such a tree. It handles the transient groups as
	efficiently as the permanent groups and will not cause CPU or
	memory congestions for the routers when there are a large
	number of source-group pairs.

	One problem our algorithm faces is that there might be certain
	conditions under which a group member receives a message with 
	prolonged delay. Because non-shortest paths are taken, when a 
	node receives a message through a much longer path than the 
	shortest path, this will be undesirable for time constraint 
	applications.  All low-cost algorithms have the same 
	problem, and there may be times at which some control must be 
	exercized to prevent it from happening.

	This algorithm has been designed  under the ``link state''
	environment, that is, every node knows the network topology 
	and the global group information. Another situation is 
	that a node only knows the state of its neighbors, which is
	where the distributed Bellman-Ford algorithm finds its
	application.  It will be useful to develop a low-cost 
	routing algorithm for such environments.

