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5 shows the inexpensive Mica2 motes densely placed along the roadway in stage one to allow for hardware failures through redundancy The goal of stage one is to detect the presence of a vehicle utilizing data from the acoustic and magnetometer sensors for cueing stage two and three sensors Vehicle classi cation may also occur during this stage The algorithms for vehicle detection and classi cation are embedded within the network in the stage one Stargate nodes The stage two nodes remain in a background collection mode and stage three nodes remain inactive until a vehicle is detected within the network by the stage one nodes This helps to minimize the false alarm rate of the radiation detection assets, as well as reducing the required energy draw of the stage three nodes..

1: 2: 3: 4: 5: 6: 7: 8: 9: 10: 11: 12: 13: 14: 15: 16: 17: 18:

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When a vehicle is detected within the sensing array, the stage one Stargate nodes transmit cues to the second stage nodes. These radiation detection nodes change state from background count collection to an active, timed-count collection. Each stage two detector node takes a radiation count while the passing vehicle is directly in front of it based upon its node location and the speed of the passing vehicle. These counts are coherently added across the network and compared to the environmental background readings [10]. If the vehicle is suspected of carrying radiological material, the stage three video camera is cued to collect an image of the offending vehicle. This image, along with the corroborating event information, is then relayed to a command-andcontrol console similar to Figure 2.6 for monitoring personnel for interdiction. In the eld, this command-and-control console is a tablet PC communicating to the network via its IEEE 802.11 radio link. Although commercially available hardware is limited in its performance and capabilities, ongoing eld experiments provide an indication that heterogeneous systems have the potential to provide low-cost, highly reliable solutions to many persistent surveillance applications. Continuing research at the Los Alamos National Laboratory is focusing on (a) the operational issues of a network such as node and network security, (b) validation studies of ef cient communication protocol schemes, (c) development of additional embedded algorithms for further event classi cation and

ack count 0, dwin 2 if consecutive DATA segment received then if ack count > 0 then record inter-arrival time end if ack count ack count + 1 if ack count=dwin then produce ACK ack count 0 end if if dwin < 4 then dwin dwin + 1 end if else produce ACK ack count 0 dwin 2 end if

There are chartists who see the head-and-shoulders formation on a monthly chart, and that is one reason for their price projections to 550 It is possible, but I do not believe it will be this month or this year Elliott wave theorists believe we will never see 10,000 in the Dow ever again Well, that could be, but let me share with you one thought Joe Granville (older investors may remember that name) was a major doom-and-gloomer back in 1980 when I got in the business He was warning that the Dow would crash even back then The Dow was at 900 As we know now, it is at 7700 That crash he warned about Never happened What s my point Try not to get bearish in the hole, and never follow the herd mentality Use common sense and always I mean always use stops.

r Initialization The MULEs go on their rst trip beaconing around their presence Nodes that receive this beacon reply back with their ID By the end of this phase, the MULEs are back at their starting points and know of all the nodes they can serve r Leader Election All the MULEs are assumed to be able to communicate with each other (ie, at least when at their initial position, the topology of the MULE network, is a clique) One of the MULEs is elected as the leader of the bunch (for instance, the MULE with the smaller ID) At this point, every MULE sends to the leader the information gathered in the rst phase r Load Balancing The leader divides the network nodes into shareable and nonshareable The shareable nodes are further classi ed according to the MULEs that can serve them.

DATA segment interarrival time sampled, and is an interarrival smoothing factor, with 0 < < 1, then we obtain i+1 = i + (1 ) i+1 (10.1)

This is the most delicate part of the algorithm, all performed locally by the leader MULE It is divided into two main parts: The rst part takes care of calculating the average number of nodes that could be assigned to each MULE The second takes care of the actual load balancing [33], determining the nodes that could be assigned to each MULE r Node Assignment As a result of the previous phase, some of the shareable nodes can be served by two MULEs In the node assignment, phase nodes that are shared by two MULEs are ordered according to their unique ID At this point the rst part of the set is assigned to the MULE of the two with the smallest ID, and the remaining nodes are assigned to the other MULE.

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