Mobile multimedia collaboration architecture and applications

The Session Initiation Protocol (SIP) has gained momentum and is being widely used both in the Internet and Next Generation Telecommunications network as the core signaling protocol. SIP operation relies on SIP servers which are responsible for forwarding of SIP messages. It has been shown that the performance of SIP servers is largely degraded during overload conditions due to the built in message retransmission mechanism of SIP. This is an obstacle in wide deployment of SIP for a realistic situation. In this paper we propose a distributed and adaptive window based overload control algorithm, which controls the amount of calls that are forwarded to a downstream SIP server in an attempt to prevent it from being overloaded. Our scheme uses the call establishment delay as a measure of the amount of load on the downstream server and unlike other methods does not rely on explicit feedback. Using simulations we show that our proposed method performs better than a commonly used overload control algorithm and exhibits fast convergence and is stable.

Data Distribution Management (DDM) is one of the most critical component of any large-scale interactive distributed simulation systems. The aim of DDM is to reduce and control the volume of information exchanged among the simulated entities (federates) in a large-scale distributed simulation system. In order to fulfill its goal, a considerable amount of DDM messages needs to be exchanged within the simulation (federation). The question of whether each message should be sent immediately after it is generated or held until it can be grouped with other DDM messages needs to be investigated further. Our experimental results have shown that the total DDM time of a simulation varies considerably depending on which transmission strategy is used. Moreover, in the case of grouping, the DDM time depends on the size of the group. In this paper, we propose a novel DDM approach, which we refer to as Adaptive Grid-based (AGB) DDM. The AGB protocol is distinct from all existing DDM implementations, because it is able to predict the average amount of data generated in each time step of a simulation. Therefore, the AGB DDM approach controls a simulation running in the most appropriate mode to achieve a desired performance. This new DDM approach consists of two adaptive control parts: 1) the Adaptive Resource Allocation Control (ARAC) scheme and 2) the Adaptive Transmission Control (ATC) scheme. The focus of this paper is on the ATC scheme. We describe how to build a switching model to predict the average amount of DDM messages generated and how the ATC scheme uses this estimation result to optimize the overall DDM time. Our experimental results provide a clear evidence that the ATC scheme is able to achieve the best performance in DDM time when compared to all existing DDM protocols using an extensive set of experimental case studies.

Voice over Internet Protocol (VoIP) over wireless mesh networks (WMNs) is becoming more and more popular due to its significant cost advantage, higher flexibility and wide coverage. One of the most basic requirements of VoIP is that it must provide privacy and security protection for VoIP clients. Unfortunately, little effort is spent on this area. In this paper, we focus on the privacy security of session initiation protocol (SIP) and propose a privacy-aware SIP called PA-SIP to enhance the VoIP privacy security. PA-SIP extends the SIP and applies a subjective logic based reputation mechanism to detect and isolate the insider malicious nodes. Finally, we analyze the PA-SIP in terms of security and performance.

Multi-casting and data distribution management (DDM) play a critical role in the design of future generations of large-scale distributed simulation systems, in which a large number of DDM messages are exchanged between the participating entities. Thus, communication overhead is one of the most challenging issues that needs to be studied and it must be investigated further whether each message should be sent immediately after it is generated during the simulation or held until it can be grouped with other DDM messages. Very little work has been done to answer these questions. Our experimental results have shown that the total DDM time of a simulation varies considerably depending on which transmission strategy is used. Moreover, in the case of message grouping, the DDM time depends on the size of the group. In this paper, we propose a novel adaptive transmission control (ATC) scheme for DDM. As opposed to previous DDM schemes, our proposed scheme has the ability to predict the average amount of DDM messages generated in each timestep of a simulation. Therefore, the ATC scheme is able to control a simulation running in the most appropriate mode to achieve a desired performance. In order to accomplish this goal, we will show how to use the switching model to predict the average amount of DDM messages generated in the grid-based DDM system. The experimental results are used to validate the correctness of the switching model and exhibit improved performance over previous schemes.

The high level architecture (HLA) standard developed by the Department of Defense in the United States is a key technology to perform distributed simulation. Inside the HLA framework, many different simulators (termed federates) may be interconnected to create a single, more complex simulator (federation). Data distribution management (DDM) is an optional subset of services that controls which federates should receive notification of state modifications made by other federates. A simple DDM implementation usually generate much more traffic than needed, while a complex one might introduce too much overhead. In this work, we describe an approach to DDM that delegates a portion of the DDM computation to a processor on the network card, in order to provide more CPU time for other federate and RTI computations, while still being able to exploit the benefits of a complex DDM implementation to reduce the amount of information exchange.

Performance analysis of an adaptive dynamic grid-based approach to data distribution management

Currently, various efforts are being performed on specifying distributed mobility management (DMM) for IPv6 mobile networks. DMM is expected to eliminate the limitations of the current IPv6 mobility protocols and to cope with the rapid increase in mobile data traffic. In current DMM approaches, the mobility anchoring is distributed at the access router level and the mobile node changes dynamically the mobility anchor for new sessions. Although such approaches avoid any network bottleneck and allow optimal routing in most cases, they lack reachability support since the mobile node has no permanent IPv6 address. In this paper, we consider one of the DMM approaches, dynamic mobility anchoring, and study the usage of session initiation protocol (SIP) for providing reachability support. After defining different SIP-based location update modes, we carry out a comparative cost analysis considering new performance metrics related to the processing loads at each network entity. We consider the location update loads on the location server as well as the context, signaling, and tunneling loads on a mobility anchor. We investigate the different modes in several scenarios, allowing the mobile network operator to adopt the preferred mode depending on their architecture.

The Empirical Case Against Asymmetric Regulation of Broadband Internet Access

Data Distribution Management (DDM) is one of the High Level Architecture (HLA) services that reduce message traffic over the network. The major purpose of the DDM is to filter the exchange of data between federates during a federation. However, this traffic reduction usually suffers from higher computational overhead when calculating the intersection between update regions and subscription regions in a matching process. In order to reduce the computational overhead for the matching process, this paper proposes a binary partition-based matching algorithm for DDM in the HLA-based distributed simulation. The new matching algorithm is fundamentally based on a divide-and-conquer approach. The proposed algorithm recursively performs binary partitioning which divides the regions into two partitions that entirely cover those regions. This approach promises low computational overhead, since it does not require unnecessary comparisons within regions in different partitions. The experimental results show that the proposed algorithm performs better than the existing DDM matching algorithms and improves the scalability of the DDM.

Data Distribution Management (DDM) is one of the High Level Architecture (HLA) services that reduce message traffic over the network. The major purpose of the DDM is to filter the exchange of data between federates during a federation. However, this traffic reduction usually suffers from higher computational overhead when calculating the intersection between update regions and subscription regions in a matching process. In order to reduce the computational overhead for the matching process, this paper proposes a binary partition-based matching algorithm for DDM in the HLA-based distributed simulation. The new matching algorithm is fundamentally based on a divide-and-conquer approach. The proposed algorithm recursively performs binary partitioning which divides the regions into two partitions that entirely cover those regions. This approach promises low computational overhead, since it does not require unnecessary comparisons within regions in different partitions. The experimental results show that the proposed algorithm performs better than the existing DDM matching algorithms and improves the scalability of the DDM.

Built-in privacy has for too long been neglected by regulators. They have concentrated on reacting to violations of rules. Even imposing severe fines will however not address the basic issue that preventative privacy protection is much more meaningful. The paper discusses this in the context of the International Working Group on Data Protection in Telecommunications (“Berlin Group”) which has published numerous recommendations on privacy-compliant design of technical innovations. Social network services, road pricing schemes, and the distribution of digital media content have figured prominently in the group’s latest working papers. More recently, a judgment of the European Court of Human Rights has thrown light on weaknesses in the protection of patients’ data in hospitals that requires urgent action by designers of IT systems. Built-in privacy is no magic button, no panacea, but it has turned out to be a necessary condition for meaningful privacy protection.

Due to the rapid increase in the amount of data that people need to deal with computing tasks, such as distributed computing, cloud computing and other technologies are more and more concerned by most people. In recent years, with people's attention to information security and personal privacy protection, cloud computing security has gradually become the focus of researchers. In the cloud computing environment, massive distributed data storage and management and data centralization autonomy can control the data mechanism, and distribute management of redundant data and transaction processing. These management and application are generally through the distributed database for actual operation, from the user's point of view, the access process to the distributed database is transparent. In fact, from the user's point of view, a single distributed database is essentially a combination of a group of databases stored on multiple computers. This paper studies the distributed data processing system based on cloud computing technology.

Broadband Internet access using ADSL or cable modems provides sufficient bandwidth for real-time video streaming. If television channels could be distributed on the Internet, each channel would get a world wide audience. However, television distribution from a single sender does not scale and IP-level multicasting is complex and costly. We propose a solution based on application-level multicasting using a P2P network, called P2P-TV. Each peer receives a video stream and must also forward this stream to others. This work presents an architecture for streaming video. Our P2P-TV proposal aims to solve three problems that are currently not addressed in other P2P streaming proposals, namely 1) maximizing the usage of all available peer bandwidth, 2) taking current network conditions into account (network awareness), and 3) the freeriding problem. Multiple description coding is an integral part of our solution. By splitting the video stream into smaller streams we can utilize all the bandwidth of a peer. Multiple streams allow more efficient adaptation of the multicast tree to current network conditions. Bittorrent-like bartering of content is also enabled by using multiple streams.

Current online transactions of aquatic products are often plagued by problems such as low efficiency, high platform supervision cost, insufficient trust and leakage of transaction data. Blockchain has been widely used in many different fields due to its decentralization, non-tampering and distributed data management. In order to resolve the existing problems, a blockchain-based aquatic product trading matching model integrated with credit mechanisms is proposed in this study to improve the efficiency, quality, security and satisfaction of online transactions for aquatic products. Then, based on this model, an online trading matching prototype system for aquatic products is developed, taking the Hyperledger Fabric as the underlying architecture. The performance testing of the prototype system has demonstrated that the introduction of the credit mechanism has a certain improvement effect on the trading matching results of aquatic products, and the system can complete more than 1000 transactions within half an hour, which can satisfy the normal business-to-business online transaction needs for aquatic products. To a certain extent, it can reduce the security risks and supervision cost, and improve the efficiency and satisfaction of online transaction. This study can also bring insights to blockchain-based online trading models in other industry fields.

The Supply Side of the Digital Divide: Is There Redlining in the Broadband Internet Access Market?