II.1 Related Work in User Mobility
In the current literature, the term ‘user mobility’ can be found in three research areas; 1. Immersive Virtual Environment, 2. cellular phone wireless mobile networks and 3. Intelligent Environment including nomadic computing, ubiquitous and pervasive computing. User mobility in this thesis has only a small relationship to user mobility in an Immersive Virtual Environment, which deals with how the users control their viewpoints to move in virtual space (Frees and Kesser 2003). This study also has only a loose relationship to user mobility in cellular phone wireless mobile networks, which enable a mobile user to communicate with others regardless of location. User mobility in this area has more mature technology than in the Intelligent Environment area. This cellular environment uses user mobility information as follows:
assisted user mobility management (traffic routing) (Shen, Mark et al. 2000; Kravets, Carter et al. 2001),
managed network resources, such as resources allocation, call admission control, congestion and flow control (Bellavista, Corradi et al. 2000; Shen, Mark et al. 2000), predicted user mobility (Liu, Bahl et al. 1998; Chan and Seneviratne 1999; Akyildiz and
Wang 2004),
user mobility patterns or movement pattern schemes (Zonoozi and Dassanayake 1997; Chan and Seneviratne 1999; Cayirci and Akyildiz 2002)
User cell change processes in micro-cells and macro-cells (Liu, Bahl et al. 1998; Cho, Chung et al. 2000; Del-Re, Fantacci et al. 2000)
Most research into user mobility in the Ubiquitous Computing area focuses on the problem of host mobility, to allow the user access to the same service while moving. However, to do this the user needs to carry the same mobile host. Cui et al. argue that this is only a special case of user mobility (Cui, Nahrstedt et al. 2004). In the Intelligent Environment, user mobility not only includes host mobility, but also includes the case where a user is free to switch from one host to another as well and move from one location or computing environment to another. Further, in the case of user mobility, a user is free to access his personalised service anytime, anywhere, through any possible mobile or fixed device (Sousa and Garlan 2002).
While the use of movement prediction seems to be a promising approach for improving the efficiency, reliability and adaptability of wireless networks, the actual user mobility client patterns are not yet well understood (Chan and Seneviratne 1999).
There are two problems with these approaches. First, since to some degree the assumption of homogenous computing baseline is used, this cannot take full advantage of the diverse capabilities of each environment, such as external displays, processors, and I/O devices. Second, the lack of ability to handle dynamic variations to capabilities and resources in the context-aware environment without overburdening the user with manual tuning and reconfiguration (Sousa and Garlan 2002; Cui, Nahrstedt et al. 2004).
A user mobility use mostly in wireless environment, which the availability of large bandwidth, low error rates and always-on connectivity exists as it has in a wired environment. Mobile user devices need to quickly detect and adapt to drastic changes in the characteristics and available resources of the wireless environment. In this study, middleware technology is considered for this purpose, as intermediary to providing higher-level network services and abstract service environments for distributed applications.
The middleware technology supports transparent service to users. This transparency builds a new form of awareness of an environment that allows the execution context and adapts to middleware behaviour. Unfortunately in executing resources and execution environments from direct application participation often results in premature termination of the problematic application if available resources are depleted. An alternative approach is to develop an event-driven mobile middleware that supports a degree of flexibility by allowing direct participation of applications in adapting to changes in resources. In the formulation of a context-aware middleware, suitable control mechanisms were required to directly participate in resources adaptation in response to the dynamic operating environment (Chan, Chuang et al. 2004). The scripting of an event service including the declarative language can be developed based on XML, which supports synchronous event call-backs, to express the conditions that are bound to a specific event in order to build a composite event from a set of primitive events.
The early event model has been introduced on agent-oriented software engineering, such as ROADMAP (Juan, Sterling et al. 2002), Gaia (Wooldridge, Jennings et al. 2000; Juan, Pearce et al. 2002), Prometheus (Padgham and Winikoff 2002). In event model, the object abstractions are on the flow and the processing of events is applied across different levels leading to the ultimate notification of events to the service objects. For example, Chuang et al. developed event platform in WebPADS (Chuang, Chan et al. 2002). When the WebPADS client starts executing, a default-service chain is created, which is based on the description in XML configuration. The default- service-chain map is attached to an environment monitor, which regulates the time and conditions that determine when reconfiguration of the service is to take place (Chan, Chuang et al. 2004), which can be used for monitoring user mobility.
The user mobility problem in Ubiquitous Computing has significant challenges in developing Active Office, for example, developing infrastructure with a variety of wired and wireless sensors, fusing sensor data using a spatio-temporal database (see Section 8.4.1), and the use of machine learning (see Section 5.2) for a variety of user locations and user activities, the use of event-driven mobile middleware for a variety of user mobility. In developing context aware systems, it also challenges because of the use of already existing devices (old sensors and networks) and new embedded devices, to develop context-aware applications, which require toolkits designed to enable maximum capability of the devices/sensors. The toolkit design should follow the requirements of the context aware applications, which are:
a. ease of deployment
d. increasing human trust in the system’s care for user privacy and security.
