Dynamic Channel Allocation for Wireless Zone Based Multicast and Broadcast Service
A B S T R A C T (See below for source code)
In wireless Multicast Broadcast Service (MBS), the common channel is used to multicast the MBS content to the Mobile Stations (MSs) on the MBS calls within the coverage area of a Base Station (BS), which causes interference to the dedicated channels serving the traditional calls, and degrades the system capacity. The MBS zone technology is proposed in Mobile Communications Network (MCN) standards to improve system capacity and reduce the hand off delay for the wireless MBS calls.
In the MBS zone technology, a group of BSs form an MBS zone, where the macro diversity is applied in the MS, the BSs synchronize to transmit the MBS content on the same common channel, interference caused by the common channel is reduced, and the MBS MSs need not perform handoff while moving between the BSs in the same MBS zone. However, when there is no MBS MS in a BS with the MBS zone technology, the transmission on the common channel wastes the bandwidth of the BS.
It is an important issue to determine the condition for the MBS Controller (MBSC) to enable the MBS zone technology by considering the QoS for traditional calls and MBS calls. In this paper, we propose two Dynamic Channel Allocation schemes: DCA and EDCA by considering the condition for enabling the MBS zone technology. Analysis and simulation experiments are conducted to investigate the performance of DCA and EDCA.
Distributed systems are composed of processes, located on one or more sites that communicate with one another to offer services to upper-layer applications. A major difficulty a system designer has to cope with in these systems lies in the capture of consistent global states from which safe decisions can be taken in order to guarantee a safe progress of the upper-layer applications. To study and investigate what can be done (and how it has to be done) in these systems when they are prone to process failures, two distributed computing models have received significant attention, namely, the synchronous model and the asynchronous model.
The synchronous distributed computing model provides processes with bounds on processing time and message transfer delay. These bounds, explicitly known by the processes, can be used to safely detect process crashes and, consequently, allow the non crashed processes to progress with safe views of the system state (such views can be obtained with some “time-lag”). In contrast, the asynchronous model is characterized by the absence of time bounds (that is why this model is sometimes called the time-free model).
In these systems, a system designer can only assume an upper bound on the number of processes that can crash (usually denoted as f) and, consequently, design protocols relying on the assumption that at least (n _ f) processes are alive (n being the total number of processes). The protocol has no means to know whether a given process is alive or not. Moreover, if more than f processes crash, there is no guarantee on the protocol behavior (usually, the protocol loses its liveliness property).
Synchronous systems are attractive because they allow system designers to solve many problems. The price that has to be paid is the a priori knowledge on time bounds. If they are violated, the upper-layer protocols may be unable to still guarantee their safety property. As they do not rely on explicit time bounds, asynchronous systems do not have this drawback. Unfortunately, they have another one, namely, some basic problems are impossible to solve in asynchronous systems.
The consensus problem can be stated as follows: Each process proposes a value, and has to decide a value, unless it crashes (termination), such that there is a single decided value (uniform agreement), and that value is a proposed value (validity). This problem, whose statement is particularly simple, is fundamental in fault-tolerant distributed computing as it abstracts several basic agreement problems. That problem is both a communication problem and an agreement problem.
Its communication part specifies that the processes can broadcast and deliver messages in such a way that the processes that do not crash deliver at least the messages they send. Its agreement part specifies that there is a single delivery order.
The functional specification is designed to be read by a general audience. Readers should understand the system, but no particular technical knowledge should be required to understand the document.
Functional Requirements should include:
Examples of Functional Requirements:
Functional requirements should include functions performed by specific screens, outlines of work-flows performed by the system and other requirements the system must meet.
Non – Functional Requirements
Non-functional requirements describe user-visible aspects of the system that are not directly related to functionality of the system.
i. User Interface:
A menu interface has been provided to the client to be user friendly.
The client is provided with an introductory help about the client interface and the user documentation has been developed through help hyperlink.
iii. Performance Constraints, Reliability:
iv. Error Handling and Extreme Conditions:
In case of User Error, the System should display a meaningful error message to the user, such that the user can correct his Error. The high level components in proposed system should handle exceptions that occur while connecting to database server, IOExceptions etc.
v. Quality Issues:
Quality issues refer to how reliable, available and robust should the system be? While developing the proposed system the developer must be able to guarantee the reliability transactions so that they will be processed completely and accurately.
The ability of system to detect failures and recovery from those failures refers to the availability of system. Robustness of system refers to the capability of system providing information when concurrent users requesting for information.
vi. Acceptance Criteria:
The developer will have to demonstrate and show to the user that the system works by testing with suitable test cases so that all conditions are satisfied.
The below links contains table of contents, UML diagrams, list of tables, screen shots, documentation and source code of Dynamic Channel Allocation for Wireless Zone Based Multicast and Broadcast Services.