This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Coverage control for mobile sensing networks

Among the panoply of applications enabled by the Internet of Things (IoT), smart and connected health care is a particularly important one. Networked sensors, either worn on the body or embedded in our living environments, make possible the gathering of rich information indicative of our physical and mental health. Captured on a continual basis, aggregated, and effectively mined, such information can bring about a positive transformative change in the health care landscape. In particular, the availability of data at hitherto unimagined scales and temporal longitudes coupled with a new generation of intelligent processing algorithms can: (a) facilitate an evolution in the practice of medicine, from the current post facto diagnose-and-treat reactive paradigm, to a proactive framework for prognosis of diseases at an incipient stage, coupled with prevention, cure, and overall management of health instead of disease, (b) enable personalization of treatment and management options targeted particularly to the specific circumstances and needs of the individual, and (c) help reduce the cost of health care while simultaneously improving outcomes. In this paper, we highlight the opportunities and challenges for IoT in realizing this vision of the future of health care.

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Health Monitoring and Management Using Internet-of-Things (IoT) Sensing with Cloud-Based Processing: Opportunities and Challenges

Computer communications

Sensors on (or attached to) mobile phones can enable attractive sensing applications in different domains, such as environmental monitoring, social networking, healthcare, transportation, etc. We introduce a new concept, sensing as a service (S2aaS), i.e., providing sensing services using mobile phones via a cloud computing system. An S2aaS cloud needs to meet the following requirements: 1) it must be able to support various mobile phone sensing applications on different smartphone platforms; 2) it must be energy-efficient; and 3) it must have effective incentive mechanisms that can be used to attract mobile users to participate in sensing activities. In this vision paper, we identify unique challenges of designing and implementing an S2aaS cloud, review existing systems and methods, present viable solutions, and point out future research directions.

Sensing as a Service: Challenges, Solutions and Future Directions

A method for perfoming mode-agile communications during a communications session is disclosed. A communications terminal device (104, 118, 124B, 124A) supporting muliple modes of access is configured to detemine when, during a session involving a first mode of access communi- cations, a second mode of access is available and is to be used for subsequent communications for the session. The communications terminal device (104, 118, 124B, 124A) initiates or controls switchover from one mode of access to another.

Fixed-mobile communications with mid-session mode switching

Sensors mounted on vehicles (e.g., buses, taxis, police cars) and public personnel (e.g., policemen) are used to monitor various conditions and situations such as air quality, potential biological and chemical attacks, and road and traffic conditions. The invention improves upon the typical approach that deploys fixed sensors at every geographical position of interest. The total number of required sensors and the size and the complexity of the network infrastructure required to connect the sensors are reduced and simplified. A method for estimating the number of mobile sensors required to cover a region of interest also is disclosed. A relatively small number of mobile sensors may be sufficient to cover a large area at a lower cost and less complexity than a fixed sensor network.

Environmental monitoring using mobile devices and network information server

In order to ensure proper quality of service for real-time communication in a mobile wireless Internet environment it is essential to minimize the transient packet loss when the mobile is moving between different cells (subnets) within a domain. Network layer mobility management schemes have been proposed to provide optimized fast-handoff for multimedia streams during a client's frequent movement within a domain. This paper introduces application layer techniques to achieve fast-handoff for real-time RTP/UDP based multimedia traffic in a SIP signaling environment. These techniques are based on standard SIP components such as user agent and proxy which usually participate to set up and tear down the multimedia sessions between the mobiles. Unlike network layer techniques, application layer techniques do not have to depend upon any additional components such as home agent and foreign agent. It thus provides a network access independent solution suitable for application service providers.

Fast-handoff schemes for application layer mobility management

In some embodiments, a system and method for substantially real-time comparison of quality of interfaces by mobile devices over heterogeneous networks is disclosed The method can be performed using a dynamic and rapid comparison by distributed hosts, using a minimal number of injected network packets, using minimal path quality metrics, which path quality metrics are independent of how a Qol is measured, and in a manner suitable for both wireline and wireless networks

Real-time comparison of quality of interfaces

A mobile device receives wireless network information from a MIIS (Media Independent Information Server), and builds its own database of existing networks with their associated characteristics, appropriately mapped with GPS (Global Positioning Satellite) coordinates or other appropriate form of geographical location identifying information. Consequently, the mobile device becomes 'smart' over time through the learning process of first attempting to utilize its own developed database and, only if such database information falls short, making a remote query to a MIIS to get required information for session continuity and performing handovers. The mobile device may store the information received from the MIIS in its own local database together with a time-stamp. Each time the mobile device needs to get updated or new information, it sends a request to the MIIS along with the time-stamp appended to the request. In this way, the mobile device is sent only the information that it does not already have stored in its database

Ip network information database in mobile devices for use with media independent information server

Systems and methods are described for secure and seamless roaming between internal and external networks. Double and triple tunnels may be used to connect a mobile node to a correspondent host. A mobile node may include the ability to connect to two networks simultaneously to enable seamless roaming between networks.

Sunil Madhani

Papers

Environmental monitoring using mobile devices and network information server

Fast-handoff schemes for application layer mobility management

Real-time comparison of quality of interfaces

Ip network information database in mobile devices for use with media independent information server

Secure and seamless wan-lan roaming