Introduction Beehive is a routing algorithm with emphasis On wireless ad-hoc mobile networks and Energy awareness. It is Completely Distributed and does not need global information about the network condition. The algorithm is based on source routing and on-demand routing.

This algorithm is inspired from honey bee behavior specially their foraging techniques. Hive sends agents to look for food and if one of them finds a good food site it returns back to hive to perform the Waggle Dance on the Dance Floor. Waggle dance Waggle dance2

This dance gives three important information :  The Direction of flower patches(angle between the sun and the patch)  The distance from the hive(duration of the dance)  The quality rating (fitness)(frequency of the dance). So the hive can easily enhance the discovered site with a sufficient number of foragers even without a guide.

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Basic idea outlines Most design decisions were done with the picture of honeybees in mind. Every node is a beehive, with packets (bees) collecting data (food). This means that every packet is a very simple mobile agent, transporting user data and route information from its starting node to its destination. Once it returns with fresh information about the route conditions, it will "inform" other bees through waggle dances, depending on the rating.

Beehive’s steps: 1- each node consider itself as a representative node (node with the lowest ip address take this position) 2- after launching 1st,2nd and 3rd short distance bee agent network is organized into fixed partition called foraging region. 3- each node has a specific foraging zone. 4- each non representative node launch periodically short distance bee agent by broadcasting replicas to the neighbors. 5- representative node launch long distance bee agent.

6- bee agent collect path information during the trip. 7- each node has three routing tables Intra Foraging Zone Inter Foraging Region Foraging Region Membership 8- each node can route any destination in the network. 9- The next hop for a data packet is selected in a probabilistic manner according to the quality measure of the neighbors. Ri Ri D1(i).. Dd(i)Dd(i) N1(i)N1(i) (p11, q11)..(p1d, q1d) Nn(i)Nn(i) (pn1, qn1)..(pnd,qnd)

IFZ+IFR node 10 FRM

pseudo code of BeeHive  t:= current time, tend:= time to end simulation  // Short Limit:= 4, Long Limit:= 10, Bee Generation Interval:= 1  // i=current node, d=destination node, s=source node  // n=successor node of i, p=predecessor node of i  // z=Representative node of the foraging region containing s  // w=Representative node of the foraging region containing d  // q is queuing delay estimate of a bee agent from node p to s  // p is propagation delay estimate of a bee agent from node p to s  Δt:= Bee Generation Interval, Δh:= hello packet generation interval  bip:=estimated link band width to neighbor p  pip:=estimated propagation delay to neighbor p  hi:= hop limit for bees of i, lip:=size normal queue i to p (bits)

foreach Node // concurrent activity over the network while (t ≤ tend) if ( t mod Δt = 0) if(i is representative node of the foraging region) set hi:= Long Limit, bi is long distance bee agent else set hi:= Short Limit, bi is short distance bee agent endif launch a bee bi to all neighbors of i endif foreach bee bs received at i from p if(bs was launched by i or its hop limit reached) kill bee bs elseif(bs is inside foraging zone of node s) Calculate q and p

Update IFZ routing table entries qps = q and pps = p Update q Update p else Calculate q and p Update IFR routing table entries qpz = q and ppz = p Update q Update p endif if( bs already visited node i) kill bee bs else use priority queues to forward bs to all neighbors of i except p endif endfor

foreach data packet dsd received at i from p if ( node d is within foraging zone of node i) consult IFZ routing table of node i to find delays to node d calculate goodness of all neighbors for reaching d using equation 2 else consult FRM routing table of node i to find node w consult IFR routing table of node i to find delays to node w calculate goodness of all neighbors for reaching w using equation 2 endif probabilistically select a neighbor n (n = p) as per goodness enqueue data packet dsd in normal queue for neighbor n endfor

if ( t mod Δh = 0) send a hello packet to all neighbors if (time out before a response from neighbor) (4th time) neighbor is down update the routing table and launch bees to inform other nodes endif endwhile Endfor

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Experiments with different test cases on these algorithms show that. 1-Bees algorithm is more efficient when finding and collecting food, that is it takes less number of steps. 2-Bees algorithm is more scalable it requires less computation time to complete task.