The order picking process has been considered as the most time-consuming and costly activity in warehouse management. Efficient location management, including product location management and storage location assignment management, serves as the key to reducing product searching time and traveling time during the process. This research is motivated by a real-life industrial case, which is from a forklift manufacturer that encountered the underperformance in warehouse management. Excessive time was consumed in searching and picking the forklift in finished product warehouse, which thus led to great waste in resources and even the postponement of delivery. To solve this problem, this paper first presents the details about the problem and related processes. A conceptual model of cloud forklifts and its life cycle oriented management platform is then proposed. Accordingly, a prototype system named cloud forklift warehouse management system (CFWMS) is built based on the proposed model. The suggested model and system architecture is designed and developed with the commonality for general warehousing processes, and therefore can be easily configured and applied to any general warehouse environment. Results and details of implementation for the real-life case are also provided to demonstrate the validity of the proposed model and CFWMS.

Urban flood control has become an important issue for both city planners and researchers as flood is one of the most severe natural disasters for large cities. Although many measures have been implemented for urban flood control, the effectiveness and efficiency is greatly hampered by the poor management of physical assets. In urban flood control, managing physical assets is challenging as it involves a complex asset base with the dispersion of asset allocations, management processes, and information systems. To address these challenges, this paper proposes an integrated asset management platform for urban flood control. Cloud technology is adopted to provide whole life cycle management of physical assets by integrating various management processes and information systems. It also enables the cooperative management between sectors. Besides, the concept of smart asset is introduced to realize remote management and real-time data collection from these assets. In the end, a case study is also given to demonstrate the working procedural of managing a typical smart asset through the proposed cloud platform.

Multi-user multiple-input multiple-output (MU-MIMO) is the latest communication technology that promises to linearly increase the wireless capacity by deploying more antennas on access points (APs). However, the large number of MIMO antennas will generate a huge amount of digital signal samples in real time. This imposes a grand challenge on the AP design by multiplying the computation and the I/O requirements to process the digital samples. This paper presents BigStation, a scalable architecture that enables realtime signal processing in large-scale MIMO systems which may have tens or hundreds of antennas. Our strategy to scale is to extensively parallelize the MU-MIMO processing on many simple and low-cost commodity computing devices. Our design can incrementally support more antennas by proportionally adding more computing devices. To reduce the overall processing latency, which is a critical constraint for wireless communication, we parallelize the MU-MIMO processing with a distributed pipeline based on its computation and communication patterns. At each stage of the pipeline, we further use data partitioning and computation partitioning to increase the processing speed. As a proof of concept, we have built a BigStation prototype based on commodity PC servers and standard Ethernet switches. Our prototype employs 15 PC servers and can support real-time processing of 12 software radio antennas. Our results show that the BigStation architecture is able to scale to tens to hundreds of antennas. With 12 antennas, our BigStation prototype can increase wireless capacity by 6.8x with a low mean processing delay of 860μs. While this latency is not yet low enough for the 802.11 MAC, it already satisfies the real-time requirements of many existing wireless standards, e.g., LTE and WCDMA.

With the increasing of physical-layer (PHY) data rate in modern wireless local area networks (WLANs) (e.g., 802.11n), the overhead of media access control (MAC) progressively degrades data throughput efficiency. This trend reflects a fundamental aspect of the current MAC protocol, which allocates the channel as a single resource at a time. This paper argues that, in a high data rate WLAN, the channel should be divided into separate subchannels whose width is commensurate with the PHY data rate and typical frame size. Multiple stations can then contend for and use subchannels simultaneously according to their traffic demands, thereby increasing overall efficiency. We introduce FICA, a fine-grained channel access method that embodies this approach to media access using two novel techniques. First, it proposes a new PHY architecture based on orthogonal frequency division multiplexing (OFDM) that retains orthogonality among subchannels while relying solely on the coordination mechanisms in existing WLAN, carrier sensing and broadcasting. Second, FICA employs a frequency-domain contention method that uses physical-layer Request to Send/Clear to Send (RTS/CTS) signaling and frequency domain backoff to efficiently coordinate subchannel access. We have implemented FICA, both MAC and PHY layers, using a software radio platform, and our experiments demonstrate the feasibility of the FICA design. Furthermore, our simulation results show FICA can improve the efficiency of WLANs from a few percent to 600% compared to existing 802.11.

This demonstration shows a novel virtualization architecture, called Multi-Purpose Access Point (MPAP), which can virtualize multiple heterogenous wireless standards based on software radio. The basic idea is to deploy a wide-band radio front-end to receive wireless signals from all wireless standards sharing the same spectrum band, and use separate software base-bands to demodulate information stream for each wireless standard. Based on software radio, MPAP consolidates multiple wireless devices into single hardware platform, and allows them to share the same general-purpose computing resource. Different software base-bands can easily communicate and coordinate with one another. Thus, it also provides better coexistence among heterogenous wireless standards. As an example, we demonstrate to use non-contiguous OFDM in 802.11g PHY to avoid the mutual interference with narrow-band ZigBee communication.

Modern communication technologies are steadily advancing the physical layer (PHY) data rate in wireless LANs, from hundreds of Mbps in current 802.11n to over Gbps in the near future. As PHY data rates increase, however, the overhead of media access control (MAC) progressively degrades data throughput efficiency. This trend reflects a fundamental aspect of the current MAC protocol, which allocates the channel as a single resource at a time.

Sora is a fully programmable, high performance software radio platform based on commodity general-purpose PC. In this demonstration, we illustrate the main features of the Sora platform that provide researchers flexible and powerful means to conduct wireless experiments at different levels with various goals. Specifically, the demonstrator will show four useful applications for wireless research that are built based on the Sora platform: 1) A capture tool that allows one to take a snapshot on a wireless channel; 2) a signal generation tool that allows one to transmit arbitrary baseband wave-form over the air, from a monophonic tone to a complex modulated frame; 3) an on-line real-time receiving application that uses the Sora User-Mode Extension; and 4) a fully featured Software radio WiFi driver (SoftWiFi) that can seamlessly inter-operate with commercial WiFi cards.

Spatial multiple access holds the promise to boost the capacity of wireless networks when an access point has multiple antennas. Due to the asynchronous and uncontrolled nature of wireless LANs, conventional MIMO technology does not work efficiently when concurrent transmissions from multiple stations are uncoordinated. In this paper, we present the design and implementation of a crosslayer system, called SAM, that addresses the challenges of enabling spatial multiple access for multiple devices in a random access network like WLAN. SAM uses a chain-decoding technique to reliably recover the channel parameters for each device, and iteratively decode concurrent frames with misaligned symbol timings and frequency offsets. We propose a new MAC protocol, called CCMA, to enable concurrent transmissions by different mobile stations while remaining backward compatible with 802.11. Finally, we implement the PHY and MAC layer of SAM using the Sora high-performance software radio platform. Our evaluation results under real wireless conditions show that SAM can improve network uplink throughput by 70% with two antennas over 802.11.

This paper presents a context-aware mobile recommender system, codenamed Magitti. Magitti is unique in that it infers user activity from context and patterns of user behavior and, without its user having to issue a query, automatically generates recommendations for content matching. Extensive field studies of leisure time practices in an urban setting (Tokyo) motivated the idea, shaped the details of its design and provided data describing typical behavior patterns. The paper describes the fieldwork, user interface, system components and functionality, and an evaluation of the Magitti prototype.