04-09-2014, 11:19 AM
BACKGROUND
[attachment=67622]
INTRODUCTION
1.1BACKGROUND
Location-aware computing involves the automatic tailoring of information and services based on the current location of the user. We have designed and implemented Rover, a system that enables location-based services, as well as the traditional time-aware, user-aware and device-aware services. To achieve system scalability to very large client sets, Rover servers are implemented in an “action-based” concurrent software architecture that enables fine-grained application-specific scheduling of tasks. We have demonstrated feasibility through implementations for both outdoor and indoor environments on multiple platforms.
A user is shopping in a mall. On entering a store, he pulls out a PDA and browses through detailed information about the products on display. Satisfied with the information, through the PDA, he makes an online purchase of the items of interest that will be subsequently shipped to his home directly. As he walks on to the next store, which happens to be a video rental store, information on newly-released movies in his favorite categories are downloaded automatically into his PDA, along with their availability information. He chooses a couple of these movies and indicates that he will pick them up at the storefront. His membership discounts are applied to the
bill, and he confirms the charge to his credit card. The intriguing aspect of this scenario is the automatic tailoring of information and services based on the current location of the user. We refer to this paradigm as location-aware computing. The different technology components needed to realize location-aware computing are present today, powered by the increasing capabilities of mobile personal computing devices and the increasing deployment of wireless connectivity (IEEE
802.11 wireless LANs [7], Bluetooth [1], Infra-red [2], Cellular services, etc.) What has hindered its ubiquitous deployment is the lack of system-wide integration of these components ina manner that scales with large user populations. In this paper, we describe the design and initial implementation
experience of such a system, which we call Rover, and discuss the impact such a system can have on the next generation of applications, devices, and users.
Location-aware, in addition to the more traditional notions of time-aware, user-aware, and device-aware. Rover has a location service that can track the location of every user, either by automated location determination technology (for example, using signal strength or time difference) or by the user manually entering current location (for example, by clicking on a map).
Available via a variety of wireless access technologies (IEEE 802.11 wireless LANs, Bluetooth, Infrared, cellular services, etc.) and devices (laptop, PDA, cellular phone, etc.), and allows roaming between the different wireless and device types. Rover dynamically chooses between different wireless links and tailors application-level information based on the device and link layer technology.
Scales to a very large client population, for example, thousands of users. Rover achieves this through fine-resolution application-specific scheduling of resources at the servers and the network.
We will use a museum tour application as an example to illustrate different aspects of Rover. We consider group of users touring the museums in Washington D.C. At a Rover registration point in a museum, each user is issued a handheld device with audio and video capabilities, say an off-the-shelf PDA available in the market today. Alternatively, if a user possesses a personal device, he can register this device and thus gain access to Rover. The devices are traceable by the Rover system. So as a user moves through the museum, information on relevant artifacts on display are made available to the user’s device in various convenient forms, for example, audio or video clips streamed to the device. Users can query the devices for building maps and optimal routes to objects of their interest. They can also reserve and purchase tickets for exhibitions and shows in the museum later in the day. The group leader can coordinate group activities by sending relevant group messages to the users. Once deployed, the system can be easily expanded to include many other different services to the users. The next section gives a description of the kinds of services that are available through Rover. The successive sections provide an overview of the Rover architecture and a description of a concurrent software architecture that has been used for system scalability. The following sections expand on particular aspects of Rover, including clients, servers, data management and multi-Rover systems. Then we describe our initial implementation experience and conclude with ongoing and future work.
1 REVIEW
At the core of invisible computing is context awareness, the concept of sensing and reacting to dynamic environments and activities. Location is a crucial component of context, and much research in the past decade has focused on location-sensing technologies, location-aware application support, and location-based applications. With numerous factors driving deployment of sensing technologies, location-aware computing may soon become a part of everyday life.
2.2 LOCATION-SENSING TECHNOLOGIES
A central problem in location-aware computing is the determination of physical location. Researchers in academia and industry have created numerous location-sensing systems that differ with respect to accuracy, coverage, frequencyof location updates, and cost of installation and maintenance.
2.2.1 Coarse-Grained Systems
For applications in open, outdoor areas, the Global Positioning System isa common choice. A GPS receiver estimates position by measuring satellite signals’ time difference of arrival. Although GPS offers near-worldwidecoverage, its performance degrades indoors and in high-rise urban areas, and receivers have a relatively long start-up time and high cost. In 1989, Roy Want, Andy Hopper, and others pioneered the study of indoor location sensing with their infrared based Active Badge system. This provides room-grained location usingwall-mounted sensors that pick up an infrared ID broadcast by tags worn by the building’s occupants. Many of the location-sensing systems developed since then are based on radio. By using base station visibility and signal strength, it is possible to locate Wi-Fi-enabled devices with accuracies from several meters to tens of meters. Bluetooth technology, which offers a shorterrange than Wi-Fi, can give more accurate positioning, but at the expense of requiring more fixed base stations to provide coverage. Inexpensive radiofrequency identification tags can be used for location determination as well by placing RFID readers at doorways and other strategic points to detect the passage of people or objects. Location information can also be derived from other types of RF infrastructures including those for mobile phones and TV broadcasts. These can be deployed over a wide area with relative ease, in contrast to technologies such as RFID that have limited transmission range. With mobile phones, Cambridge Positioning Systems has demonstrated location accuracies of 20meters, while Rosum has achieved accuracies from 3 to 25 meters with digital TV signals.
DEPLOYMENT
Figure 1 shows Each box’s horizontal span shows the range of accuracies the technology covers; the bottom boundary represents current deployment, while the top boundary shows predicted deployment over the next several years and the current and predicted deployment of location-sensing technologies within the next two to three years. The widest existing deployments are based on GPS, which is particularly suited for outdoor applications. These include servicing applications centered on vehicle location such as route planning and fleet tracking, as well as applications integrated into handheld GPS units. Other current deployments are found in vertically integrated solutions and comprise a specific location-aware application, appropriate location-sensitive ing hardware, and a custom software platform. A handful of firms offer these systems in targeted application areas such as military training, human-body motion capture, supply chain management, and asset tracking. Looking ahead, numerous factor are accelerating the adoption of coarse-grained location-sensing technologies. To begin with, the recent explosion of Wi-Fi, Bluetooth, and other wireless networking technologies has led to many end-user devices being equipped with RF hardware that can be used for location sensing. In addition, the Enhanced 911 requirement—which mandates that US wireless carriers provide location accuracies of 50 to 100 meters for emergency 911 calls by the end of 2005— is driving incorporation of location sensing systems into mobile phones using GPS, base-station triangulation methods, and a combination of these technologies known as Assisted GPS. Similar requirements exist in the European Union.
ACTION MODEL
In order to achieve fine-grained real-time application-specific scheduling, the Rover controller is built according to concurrent software architecture we call the action model. In this model, scheduling is done in “atomic” units called actions. An action is a “small” piece of code that does not have any intervening I/O operations. Once an action begins execution, it cannot be pre-empted by another action. Consequently, given a specific server platform, it is easy to accurately bound the execution time of an action. The actions are executed in a controlled manner by an Action Controller.
We use the term server operation to refer to a transaction, either client- or administrator-initiated, that interacts with the Rover controller; examples in the museum scenario would be register Device, get Route and locate User. A server operation consists of a sequence (or more precisely, a partial order) of actions interleaved by asynchronous I/O events. Each server operation has exactly one “response handling” action for handling all I/O event responses for the operation; i.e., the action is eligible to execute whenever an I/O response is received.
A server operation at any given time has zero or more actions eligible to be executed. A server operation is in one of the following three states:
-Ready-to-run: At least one action of the server operation is eligible to be executed but no action of the server operation is executing.
-Running: One action of the server operation is executing (in a multi-processor setup, several actions of the operation can be executing simultaneously).
4 ROVER CLIENTS
The client devices in Rover are handheld units of varying form factors, ranging from powerful laptops to simple cellular phones. They are categorized by the Rover controller based on attributes identified in the device profiles, such as display properties—screen size and color capabilities, text and graphics capabilities, processing capabilities — ability to handle vector representations and image compression, audio and video delivery capabilities and user interfaces.
The Rover controller uses these attributes to provide responses to clients in the most compatible formats.
For the wireless interface of client devices, we have currently considered two link layer technologies —IEEE 802.11 Wireless LAN and Bluetooth. Bluetooth is power efficient and is therefore better at conserving client battery power. According to current standards, it can provide bandwidths of up to 2 Mbps. In contrast, IEEE 802.11 wireless is less power-efficient but is widely deployed and can currently provide bandwidths of up to 11 Mbps. In areas where these high bandwidth alternatives are not available, Rover client devices will use the lower bandwidth air interfaces provided by cellular wireless technologies that use CDMA [11] or TDMA based techniques. In particular, cellular phones can connect as clients to Rover, which implies that the Rover system interfaces with cellular service providers.
Different air-interfaces may be present in a single Rover system or in different domains of a multi-Roversystem. In either case, software radios [8] is an obvious choice to integrate different air-interfacetechnologies. While the location management system is not tied to a particular air interface, certain properties of specific air interfaces can be leveraged to better provide location management (discussed in the Appendix).
CONCLUSION AND FUTURE WORK
Location-aware computing involves the automatic tailoring of information and services based on the currentlocation of the user. We have designed and implemented Rover, a system that enables location-basedservices, as well as the traditional time-aware, user-aware and device-aware services. To achieve systemscalability to very large client sets, Rover servers are implemented in an “action-based” concurrent softwarearchitecture that enables fine-grained application-specific scheduling of tasks. We have demonstratedfeasability through implementations for both outdoor and indoor environments on multiple platforms.
Rover is currently available as a deployable system using specific technologies, both indoors and outdoors. Our final goal is to provide a completely integrated system that operates under different technologies, and allows a seamless experience of location aware computing to clients as they move through the system. With this in mind, we are continuing our work in a number of different directions. We are experimenting with a wide range of client devices, especially the ones with limited capabilities. Weare also experimenting with other alternative wireless access technologies including a Bluetooth-based LAN. We are also working on the design and implementation of a multi-Rover system.
We believe that Rover Technology will greatly enhance the user experience in a large number places, including visits to museums, amusement and theme parks, shopping malls, game fields, offices and business centers. The system has been designed specifically to scale to large user populations. Therefore, we expect the benefits of this system to be higher in such large user population environments.
[attachment=67622]
INTRODUCTION
1.1BACKGROUND
Location-aware computing involves the automatic tailoring of information and services based on the current location of the user. We have designed and implemented Rover, a system that enables location-based services, as well as the traditional time-aware, user-aware and device-aware services. To achieve system scalability to very large client sets, Rover servers are implemented in an “action-based” concurrent software architecture that enables fine-grained application-specific scheduling of tasks. We have demonstrated feasibility through implementations for both outdoor and indoor environments on multiple platforms.
A user is shopping in a mall. On entering a store, he pulls out a PDA and browses through detailed information about the products on display. Satisfied with the information, through the PDA, he makes an online purchase of the items of interest that will be subsequently shipped to his home directly. As he walks on to the next store, which happens to be a video rental store, information on newly-released movies in his favorite categories are downloaded automatically into his PDA, along with their availability information. He chooses a couple of these movies and indicates that he will pick them up at the storefront. His membership discounts are applied to the
bill, and he confirms the charge to his credit card. The intriguing aspect of this scenario is the automatic tailoring of information and services based on the current location of the user. We refer to this paradigm as location-aware computing. The different technology components needed to realize location-aware computing are present today, powered by the increasing capabilities of mobile personal computing devices and the increasing deployment of wireless connectivity (IEEE
802.11 wireless LANs [7], Bluetooth [1], Infra-red [2], Cellular services, etc.) What has hindered its ubiquitous deployment is the lack of system-wide integration of these components ina manner that scales with large user populations. In this paper, we describe the design and initial implementation
experience of such a system, which we call Rover, and discuss the impact such a system can have on the next generation of applications, devices, and users.
Location-aware, in addition to the more traditional notions of time-aware, user-aware, and device-aware. Rover has a location service that can track the location of every user, either by automated location determination technology (for example, using signal strength or time difference) or by the user manually entering current location (for example, by clicking on a map).
Available via a variety of wireless access technologies (IEEE 802.11 wireless LANs, Bluetooth, Infrared, cellular services, etc.) and devices (laptop, PDA, cellular phone, etc.), and allows roaming between the different wireless and device types. Rover dynamically chooses between different wireless links and tailors application-level information based on the device and link layer technology.
Scales to a very large client population, for example, thousands of users. Rover achieves this through fine-resolution application-specific scheduling of resources at the servers and the network.
We will use a museum tour application as an example to illustrate different aspects of Rover. We consider group of users touring the museums in Washington D.C. At a Rover registration point in a museum, each user is issued a handheld device with audio and video capabilities, say an off-the-shelf PDA available in the market today. Alternatively, if a user possesses a personal device, he can register this device and thus gain access to Rover. The devices are traceable by the Rover system. So as a user moves through the museum, information on relevant artifacts on display are made available to the user’s device in various convenient forms, for example, audio or video clips streamed to the device. Users can query the devices for building maps and optimal routes to objects of their interest. They can also reserve and purchase tickets for exhibitions and shows in the museum later in the day. The group leader can coordinate group activities by sending relevant group messages to the users. Once deployed, the system can be easily expanded to include many other different services to the users. The next section gives a description of the kinds of services that are available through Rover. The successive sections provide an overview of the Rover architecture and a description of a concurrent software architecture that has been used for system scalability. The following sections expand on particular aspects of Rover, including clients, servers, data management and multi-Rover systems. Then we describe our initial implementation experience and conclude with ongoing and future work.
1 REVIEW
At the core of invisible computing is context awareness, the concept of sensing and reacting to dynamic environments and activities. Location is a crucial component of context, and much research in the past decade has focused on location-sensing technologies, location-aware application support, and location-based applications. With numerous factors driving deployment of sensing technologies, location-aware computing may soon become a part of everyday life.
2.2 LOCATION-SENSING TECHNOLOGIES
A central problem in location-aware computing is the determination of physical location. Researchers in academia and industry have created numerous location-sensing systems that differ with respect to accuracy, coverage, frequencyof location updates, and cost of installation and maintenance.
2.2.1 Coarse-Grained Systems
For applications in open, outdoor areas, the Global Positioning System isa common choice. A GPS receiver estimates position by measuring satellite signals’ time difference of arrival. Although GPS offers near-worldwidecoverage, its performance degrades indoors and in high-rise urban areas, and receivers have a relatively long start-up time and high cost. In 1989, Roy Want, Andy Hopper, and others pioneered the study of indoor location sensing with their infrared based Active Badge system. This provides room-grained location usingwall-mounted sensors that pick up an infrared ID broadcast by tags worn by the building’s occupants. Many of the location-sensing systems developed since then are based on radio. By using base station visibility and signal strength, it is possible to locate Wi-Fi-enabled devices with accuracies from several meters to tens of meters. Bluetooth technology, which offers a shorterrange than Wi-Fi, can give more accurate positioning, but at the expense of requiring more fixed base stations to provide coverage. Inexpensive radiofrequency identification tags can be used for location determination as well by placing RFID readers at doorways and other strategic points to detect the passage of people or objects. Location information can also be derived from other types of RF infrastructures including those for mobile phones and TV broadcasts. These can be deployed over a wide area with relative ease, in contrast to technologies such as RFID that have limited transmission range. With mobile phones, Cambridge Positioning Systems has demonstrated location accuracies of 20meters, while Rosum has achieved accuracies from 3 to 25 meters with digital TV signals.
DEPLOYMENT
Figure 1 shows Each box’s horizontal span shows the range of accuracies the technology covers; the bottom boundary represents current deployment, while the top boundary shows predicted deployment over the next several years and the current and predicted deployment of location-sensing technologies within the next two to three years. The widest existing deployments are based on GPS, which is particularly suited for outdoor applications. These include servicing applications centered on vehicle location such as route planning and fleet tracking, as well as applications integrated into handheld GPS units. Other current deployments are found in vertically integrated solutions and comprise a specific location-aware application, appropriate location-sensitive ing hardware, and a custom software platform. A handful of firms offer these systems in targeted application areas such as military training, human-body motion capture, supply chain management, and asset tracking. Looking ahead, numerous factor are accelerating the adoption of coarse-grained location-sensing technologies. To begin with, the recent explosion of Wi-Fi, Bluetooth, and other wireless networking technologies has led to many end-user devices being equipped with RF hardware that can be used for location sensing. In addition, the Enhanced 911 requirement—which mandates that US wireless carriers provide location accuracies of 50 to 100 meters for emergency 911 calls by the end of 2005— is driving incorporation of location sensing systems into mobile phones using GPS, base-station triangulation methods, and a combination of these technologies known as Assisted GPS. Similar requirements exist in the European Union.
ACTION MODEL
In order to achieve fine-grained real-time application-specific scheduling, the Rover controller is built according to concurrent software architecture we call the action model. In this model, scheduling is done in “atomic” units called actions. An action is a “small” piece of code that does not have any intervening I/O operations. Once an action begins execution, it cannot be pre-empted by another action. Consequently, given a specific server platform, it is easy to accurately bound the execution time of an action. The actions are executed in a controlled manner by an Action Controller.
We use the term server operation to refer to a transaction, either client- or administrator-initiated, that interacts with the Rover controller; examples in the museum scenario would be register Device, get Route and locate User. A server operation consists of a sequence (or more precisely, a partial order) of actions interleaved by asynchronous I/O events. Each server operation has exactly one “response handling” action for handling all I/O event responses for the operation; i.e., the action is eligible to execute whenever an I/O response is received.
A server operation at any given time has zero or more actions eligible to be executed. A server operation is in one of the following three states:
-Ready-to-run: At least one action of the server operation is eligible to be executed but no action of the server operation is executing.
-Running: One action of the server operation is executing (in a multi-processor setup, several actions of the operation can be executing simultaneously).
4 ROVER CLIENTS
The client devices in Rover are handheld units of varying form factors, ranging from powerful laptops to simple cellular phones. They are categorized by the Rover controller based on attributes identified in the device profiles, such as display properties—screen size and color capabilities, text and graphics capabilities, processing capabilities — ability to handle vector representations and image compression, audio and video delivery capabilities and user interfaces.
The Rover controller uses these attributes to provide responses to clients in the most compatible formats.
For the wireless interface of client devices, we have currently considered two link layer technologies —IEEE 802.11 Wireless LAN and Bluetooth. Bluetooth is power efficient and is therefore better at conserving client battery power. According to current standards, it can provide bandwidths of up to 2 Mbps. In contrast, IEEE 802.11 wireless is less power-efficient but is widely deployed and can currently provide bandwidths of up to 11 Mbps. In areas where these high bandwidth alternatives are not available, Rover client devices will use the lower bandwidth air interfaces provided by cellular wireless technologies that use CDMA [11] or TDMA based techniques. In particular, cellular phones can connect as clients to Rover, which implies that the Rover system interfaces with cellular service providers.
Different air-interfaces may be present in a single Rover system or in different domains of a multi-Roversystem. In either case, software radios [8] is an obvious choice to integrate different air-interfacetechnologies. While the location management system is not tied to a particular air interface, certain properties of specific air interfaces can be leveraged to better provide location management (discussed in the Appendix).
CONCLUSION AND FUTURE WORK
Location-aware computing involves the automatic tailoring of information and services based on the currentlocation of the user. We have designed and implemented Rover, a system that enables location-basedservices, as well as the traditional time-aware, user-aware and device-aware services. To achieve systemscalability to very large client sets, Rover servers are implemented in an “action-based” concurrent softwarearchitecture that enables fine-grained application-specific scheduling of tasks. We have demonstratedfeasability through implementations for both outdoor and indoor environments on multiple platforms.
Rover is currently available as a deployable system using specific technologies, both indoors and outdoors. Our final goal is to provide a completely integrated system that operates under different technologies, and allows a seamless experience of location aware computing to clients as they move through the system. With this in mind, we are continuing our work in a number of different directions. We are experimenting with a wide range of client devices, especially the ones with limited capabilities. Weare also experimenting with other alternative wireless access technologies including a Bluetooth-based LAN. We are also working on the design and implementation of a multi-Rover system.
We believe that Rover Technology will greatly enhance the user experience in a large number places, including visits to museums, amusement and theme parks, shopping malls, game fields, offices and business centers. The system has been designed specifically to scale to large user populations. Therefore, we expect the benefits of this system to be higher in such large user population environments.