New Standoff for Countersunk Hole and Stacking Process

Sometimes we are requested to leverage an existing cage from current project but need to add standoff in the location of countersunk hole. Traditional standoff couldn’t stack well on the countersunk hole. The torque out force will be low and not complying with our requirement. This is why we disclosure this technology

Easy Connect Vertical Drive Cage

An Easy Connect Vertical Drive Cage allows storage drives and cages to interlock together for better mechanical support

CITRIC: A low-bandwidth wireless camera network platform

In this paper, we propose and demonstrate a novel wireless camera network system, called CITRIC. The core component of this system is a new hardware platform that integrates a camera, a frequency-scalable (up to 624 MHz) CPU, 16 MB FLASH, and 64 MB RAM onto a single device. The device then connects with a standard sensor network mote to form a camera mote. The design enables in-network processing of images to reduce communication requirements, which has traditionally been high in existing camera networks with centralized processing. We also propose a back-end client/server architecture to provide a user interface to the system and support further centralized processing for higher-level applications. Our camera mote enables a wider variety of distributed pattern recognition applications than traditional platforms because it provides more computing power and tighter integration of physical components while still consuming relatively little power. Furthermore, the mote easily integrates with existing low-bandwidth sensor networks because it can communicate over the IEEE 802.15.4 protocol with other sensor network platforms. We demonstrate our system on three applications: image compression, target tracking, and camera localization

Moving Forward

This lecture surveys several research areas in communication networking research. First, we covered an example of proposals to change the routing topology of the internet away from shortest path routing to reduce congestion bottlenecks. Then, we covered issues when networking under different types of environments and with different types of constraints/requirements: mobile networking, network security, quality of service (QoS), and wireless networking. This was followed by a discussions of some issues with transitioning/patching old network deployments and incorporating economics for pricing networks. Lastly, we briefly touched on some related research areas that might intersect networking research. I. TOPOLOGY The 100 × 100 project [1] is a proposal to link 100 million homes with 100 Megabit/second internet connections. In this proposal, instead of using shortest path routing for the internet backbone, the network would use a two-step routing strategy to spread out network traffic so that the network load is more uniform. This two step strategy involves first routing packets from the source to a random switch, and then routing packets from the random switch to the final destination (See Figure 1). This idea was borrowed from a similar proposal for routing data between microprocessors. In addition to this change in routing, the 100x100 project proposes to apply local back pressure/feedback to reduce congestion as opposed to only applying end-to-end back pressure to reduce congestion in TCP. The 100 × 100 project is meant to replace OSPF and BGP. Of course, there are costs and technical limitations to be considered for these proposed changes to the routing protocols. For instance, a maximum optical fiber length of around 500 km limits the selection of random switches for routing by the source. Also, the random routing in the first step of the routing scheme needs the switches in the internet backbone to be connected, which makes adding new switches to scale the network more difficult. Many other questions remain, including how many switching centers are needed and the costs for deploying this new routing topology. Fig. 1. The routing principle for the 100x100 project involves first routing to a random destination and then to the final destination to distribute network load

A Scalable Real-Time Multiple-Target Tracking Algorithm for Sensor Networks

Multiple-target tracking is a representative real-time application of sensor networks as it exhibits different aspects of sensor networks such as event detection, sensor information fusion, multi-hop communication, sensor management and real-time decision making. The task of tracking multiple objects in a sensor network is challenging due to constraints on a sensor node such as short communication and sensing ranges, a limited amount of memory and limited computational power. In addition, since a sensor network surveillance system needs to operate autonomously without human operators, it requires an autonomous real-time tracking algorithm which can track an unknown number of targets. In this paper, we develop a scalable real-time multiple-target tracking algorithm that is autonomous and robust against transmission failures, communication delays and sensor localization error. In particular, there is no performance loss up to the average localization error of.7 times the separation between sensors and the algorithm tolerates up to 50 % lost-to-total packet ratio and 90 % delayed-to-total packet ratio