A caching and streaming framework for mulitmedia

Real Time streaming Protocol (RTSP) is the de facto standard for streaming and almost all the set up boxes and media players support it. RTSP is a very simple text based protocol for streaming. And this simplicity is one of the main reasons for the popularity of the protocol. We propose the use of RTSP along with Real Time Protocol (RTP) for Adaptive Forward Error Correction (AFEC) based streaming. The idea is to use the existing semantics of the protocol with minimal overloading to achieve the goal. The use of the RTP is solely to provide a mechanism for the packet sequence number, which is the main requirement to ensure reliability. Since, we will be using existing protocol semantics (overloading the existing semantics), we do not have the luxury of using Negative Acknowledgements (NACKs) or information rich packet headers. However, we can add the intelligence in the client/server to interpret the overloaded data and achieve the same results.

To facilitate learning with video streaming, a transport protocol that can send video is needed, such as HTTP (Hyper Text Transfer Protocol) or RTSP (Real Time Streaming Protocol). Both protocols have their respective advantages and disadvantages when sent over a MANET network. One of them is that the throughput on RTSP is greater but the use of memory is more, this is inversely proportional to the RTSP protocol. In this study, the delay value in scheme 1 HTTP and RTSP protocols has an average delay of 23.225 seconds and 19.075 seconds. The throughput has an average value of 699.165 kbps and 802.656 kbps. Packet loss has an average value of 0.428% and 17.9%. For the use of transmit power nodes have an average of -33 dBm and -31.25 dBm. Memory usage has an average value of 108.46 Mb and 149.6 Mb.While in scheme 2 the delay values for HTTP and RTSP protocols are 28 seconds and 26.1 seconds on average. Throughput 1186,803 kbps and 1316,076 kbps. Packet loss has an average value of 0.0325% and 18.69%. On the use of transmit power nodes have an average of -34 dBm and -32 dBm. Memory usage has an average value of 107.525 Mb and 154.275 Mb.

This memorandum defines the Real-Time Streaming Protocol (RTSP) version 2.0, which obsoletes RTSP version 1.0 defined in RFC 2326.RTSP is an application-layer protocol for the setup and control of the delivery of data with real-time properties.RTSP provides an extensible framework to enable controlled, on-demand delivery of real-time data, such as audio and video.Sources of data can include both live data feeds and stored clips.This protocol is intended to control multiple data delivery sessions; provide a means for choosing delivery channels such as UDP, multicast UDP, and TCP; and provide a means for choosing delivery mechanisms based upon RTP (RFC 3550).

Networking of MPEG-4 content is the topic of ongoing standardization efforts in the ISO MPEG and IETF. In this paper, we describe a complete architecture for the transport of MPEG-4 content over the Internet. The MPEG-4 concept of separation between applications and delivery mechanism is preserved. The use of well-established Internet protocols, such as the real time protocol (RTP) and the real time streaming protocol (RTSP) allows for robustness and flexibility in view of interoperability and future extensions. In particular, we present an original proposal for the mapping of MPEG-4 specific signaling primitives onto RTSP functions.

Este trabalho apresenta uma implementação de um protótipo de sistema de informação para Ambient Assisted Living (AAL) capaz de identificar em tempo real a partir de qualquer câmera com endereçamento IP que implemente o protocolo Real Time Streaming Protocol (RTSP), possíveis quedas em um ambiente monitorado e treinado. Após uma ocorrência de possível queda, o protótipo gera um alerta para um contato de emergência cadastrado.

The Active Service Environment Management system (ASEMA) provides best possible multimedia service experience to end user. One of the main aspects of the ASEMA is to provide a variable live streaming service to the end users of the ASEMA. The ASEMA implements this through dynamic change in the properties of the video stream delivered to the end user's end device. The live video stream used in the ASEMA is delivered to the end users is in MPEG 4 video format. The video itself is streamed on top of the real time protocol (RTP) and the parameters are negotiated with the real time streaming protocol (RTSP) before the streaming commences. The research problem of this is to provide easy solution for QoS measurements in networks that are closed nature. The research is based on the constructive method of the related publications and the results are deducted from the constructed quality of service management of the ASEMA system. The management is founded on the measuring of the receiving and sending bit rate values in both ends, in the sending end and in the receiving end. If a fluctuation in the values are detected the video stream's properties are changed dynamically.

This document defines Signaling Compression (SigComp), a solution for compressing messages generated by application protocols such as the Session Initiation Protocol (SIP) (RFC 3261) and the Real Time Streaming Protocol (RTSP) (RFC 2326). The architecture and prerequisites of SigComp are outlined, along with the format of the SigComp message.

This paper describes the implementation of IOCP based a MPEG-4 RTSP(Real Time Streaming Protocol) system for mobile environment. To prevent the status of cut-off and delay due to a number of contemporary users, we designed and implemented IOCP(I/O Completion Port) based MMS system which supports user access to the internal structure of RTSP through fast and small thread to enhance the performance of RTSP socket connection. This paper provides portability of MPEG-4 FGS coding scheme into mobile environment such CDMA based internet.

According to the demand of modern greenhouse information management, a greenhouse remote monitoring system was developed based on Android. This system consists of local monitoring module, server and Android client. The local monitoring module accomplishes data acquisition and device control through CAN bus, and interacts with Android client via the MySQL database. Media streaming server is developed using Real Time Streaming Protocol (RTSP) to achieve the greenhouse remote video monitoring. Android client with user-friendly interfaces can realize real-time data display, historical data query, parameter setting, device control, video monitoring etc. Using this system, people can realize real-time and long-distance scientific management of greenhouse. And the labor intensity can be reduced, what is more, the level of greenhouse automation monitoring can be improved.

Internet Telephony: Architecture and protocols—an IETF perspective

The objective of this paper is to provide a uniform means of transmitting data (audio, video) to real time constraints over multicast or unicast network services and providing much enhanced experience of the Real-time communication over the existing systems. In this paper we will explore usage of the dominating technologies in the real time systems and shows how to design and develop communications within such systems. In particular, it proposes reliable protocol over UDP transport layer that gains less than one millisecond average round trip time (RTT) and processes dozens of thousands of messages every second at each and every port in network. This paper presents the current internet protocols: Real-time Transport Protocol (RTP), RTP Control Protocol (RTCP) and Real-time Streaming Protocol (RTSP). Together these protocols may provide controlled delivery of multimedia traffic over the Internet. The feedback mechanisms for the quality of service (QoS) monitoring, such as delay, jitter and packet loss calculations, are described in detail.

By rapid growth of the Internet users and devices, thenumber of servers also increase simultaneously which causes the exponentialincrement of the internet traffic and static data. Handling these huge amountsof user requests and efficiently responding to them require high bandwidthlinks, powerful servers and robust equipment, which despite the availability ofthese requirements getting the full user satisfaction is extremely difficultand a tough challenge. In order to overcome the mentioned problem, the cacheservers are being used as a suitable solution. The performance of web cacheserver directly depends on its replacement policies. Several cache replacementpolicies have been proposed in literature each having varied hit rate (HR) andbyte hit rate (BHR) performances on different networks. The replacement policyproposed in this paper is a dynamic cache replacement policy which trainsitself utilizing previous network logs and by exploiting the data miningclustering algorithm. Once the training step is completed, the proposed policyutilizes the normalization formulas to score each metric of the enquiriesincluding recency, frequency, size and delay. Simulation results showed thatthe proposed policy has the optimum performance on different networks and itnot only improved the performance of web cache server in term of HR and BHR,but also decreases the data retrieval time (Delay Ratio (DR)) of the cacheservers.

Access to the internet and WWW is growing extensively, which results in heavy network traffic. To reduce the network traffic proxy server is used. Proxy server reduces the load of server. If the cache replacement algorithm of proxy server's cache is efficient then proxy server will be helpful to reduce the network traffic in more efficient manner. In this paper we are considering proxy server cache to be Level 1 (L1) cache and storage cache of proxy server to be Level 2 (L2) cache. For collecting the real trace CC proxy server is used in an organization. Log of proxy server gives the information of various URLs accessed by various clients with time. For performing experiments various URLs were given a numeric identity. This paper proposes an efficient replacement algorithm on L1 for proxy server. The replacement algorithms taken into consideration are Least Recently Used (LRU), Least Frequently Used (LFU), First In First Out (FIFO). Access Pattern of L1 and L2 are different as if the desired page is not on L1 then it accesses to L2. Thus L1 is having better temporal locality than L2. Thus the replacement algorithm which is giving efficient results for L1 may not be suitable for L2. This paper also proposes a preeminent pair of replacement algorithms for L1 and L2 cache for proxy server.

There are innumerable objects found on the Web. Both the popular objects that are requested frequently by the users and unpopular objects that are rarely requested exist. Hot spots are produced whenever huge numbers of objects are requested by the users. Often this situation produces excessive load on the cache server and original server, resulting in the system becoming a swamped state. Many problems arise, such as server refusals or slow operations. In this paper, a neural network prediction algorithm is suggested in order to solve the problems caused by the hot spot. The hot spot would be requested in the near future is prefetched to the proxy servers after the prediction of the hot spot; then the fast response for the users' requests and a higher efficiency for the proxy server can be achieved. The hot spots are obtained by analyzing the access logs file. A simulator is developed to validate the performance of the suggested algorithm, through which the hit rate improvement and the request among the shared proxy servers are load-balanced.

Three directory schemes are investigated: the local cache (LC) scheme in which there is a cache at the network nodes to store the results of a previous query for a remote resource so that a subsequent query for that resource can be resolved locally, and two enhancements of this scheme, namely the regional cache server (RCS) scheme and the cooperating cache servers (CCS) scheme, in which the queries not resolved locally are funneled through designated nodes or servers to reduce multiple network searchers for a given resource. The performance of these schemes in terms of the network search rate is dependent on the cache sizes at the nodes and servers, the probability distribution for queuing resources, and the cache replacement policy used to displace resources from the cache to accommodate newly discovered ones. Two policies are investigated: A/sub 0/, which is the optimal policy for the LC scheme, and the least recently used policy, which is of practical importance. >