This paper describes current and proposed protocols for mobility management for public land mobile network (PLMN)-based networks, mobile Internet protocol (IP) wireless asynchronous transfer mode (ATM) and satellite networks. The integration of these networks will be discussed in the context of the next evolutionary step of wireless communication networks. First, a review is provided of location management algorithms for personal communication systems (PCS) implemented over a PLMN network. The latest protocol changes for location registration and handoff are investigated for mobile IP followed by a discussion of proposed protocols for wireless ATM and satellite networks. Finally, an outline of open problems to be addressed by the next generation of wireless network service is discussed.

http://www.cs.tcd.ie/~htewari/papers/ieee99.pdf

Mobility management in next-generation wireless systems

Large-scale data analytics frameworks are shifting towards shorter task durations and larger degrees of parallelism to provide low latency. Scheduling highly parallel jobs that complete in hundreds of milliseconds poses a major challenge for task schedulers, which will need to schedule millions of tasks per second on appropriate machines while offering millisecond-level latency and high availability. We demonstrate that a decentralized, randomized sampling approach provides near-optimal performance while avoiding the throughput and availability limitations of a centralized design. We implement and deploy our scheduler, Sparrow, on a 110-machine cluster and demonstrate that Sparrow performs within 12% of an ideal scheduler.

/pdf/sparrow-distributed-low-latency-scheduling-4vk7xou9d2.pdf

Sparrow: distributed, low latency scheduling

A packet-centric wireless system includes: a wireless base station communicating via a transmission control protocol/internet protocol (TCP/IP) to a first data network; one or more host workstations communicating via TCP/IP to the first data network; one or more subscriber customer premise equipment (CPE) stations coupled with the wireless base station over a shared bandwidth via TCP/IP over a wireless medium; and one or more subscriber workstations coupled via TCP/IP to each of the subscriber CPE stations over a second network. The system can allocate shared bandwidth among the subscriber CPE stations to optimize end-user quality of service (QoS). The first data network includes at least one of: a wireline network; a wireless network; a local area network (LAN); and a wide area network (WAN). The second network includes at least one of: a wireline network; a wireless network; a local area network (LAN); and a wide area network (WAN).

Transmission control protocol/internet protocol (tcp/ip) packet-centric wireless point to multi-point (ptmp) transmission system architecture

Recent research on Internet traffic classification algorithms has yield a flurry of proposed approaches for distinguishing types of traffic, but no systematic comparison of the various algorithms. This fragmented approach to traffic classification research leaves the operational community with no basis for consensus on what approach to use when, and how to interpret results. In this work we critically revisit traffic classification by conducting a thorough evaluation of three classification approaches, based on transport layer ports, host behavior, and flow features. A strength of our work is the broad range of data against which we test the three classification approaches: seven traces with payload collected in Japan, Korea, and the US. The diverse geographic locations, link characteristics and application traffic mix in these data allowed us to evaluate the approaches under a wide variety of conditions. We analyze the advantages and limitations of each approach, evaluate methods to overcome the limitations, and extract insights and recommendations for both the study and practical application of traffic classification. We make our software, classifiers, and data available for researchers interested in validating or extending this work.

Internet traffic classification demystified: myths, caveats, and the best practices

Climate change and environmental monitoring and management have received much attention recently, and an integrated information system (IIS) is considered highly valuable. This paper introduces a novel IIS that combines Internet of Things (IoT), Cloud Computing, Geoinformatics [remote sensing (RS), geographical information system (GIS), and global positioning system (GPS)], and e-Science for environmental monitoring and management, with a case study on regional climate change and its ecological effects. Multi-sensors and Web services were used to collect data and other information for the perception layer; both public networks and private networks were used to access and transport mass data and other information in the network layer. The key technologies and tools include real-time operational database (RODB); extraction-transformation-loading (ETL); on-line analytical processing (OLAP) and relational OLAP (ROLAP); naming, addressing, and profile server (NAPS); application gateway (AG); application software for different platforms and tasks (APPs); IoT application infrastructure (IoT-AI); GIS and e-Science platforms; and representational state transfer/Java database connectivity (RESTful/JDBC). Application Program Interfaces (APIs) were implemented in the middleware layer of the IIS. The application layer provides the functions of storing, organizing, processing, and sharing of data and other information, as well as the functions of applications in environmental monitoring and management. The results from the case study show that there is a visible increasing trend of the air temperature in Xinjiang over the last 50 years (1962-2011) and an apparent increasing trend of the precipitation since the early 1980s. Furthermore, from the correlation between ecological indicators [gross primary production (GPP), net primary production (NPP), and leaf area index (LAI)] and meteorological elements (air temperature and precipitation), water resource availability is the decisive factor with regard to the terrestrial ecosystem in the area. The study shows that the research work is greatly benefited from such an IIS, not only in data collection supported by IoT, but also in Web services and applications based on cloud computing and e-Science platforms, and the effectiveness of monitoring processes and decision-making can be obviously improved. This paper provides a prototype IIS for environmental monitoring and management, and it also provides a new paradigm for the future research and practice; especially in the era of big data and IoT.

An Integrated System for Regional Environmental Monitoring and Management Based on Internet of Things

A prototype microcellular wireless asynchronous transfer mode network (WATMnet) capable of providing integrated multimedia communication services to mobile terminals is described in this paper. The experimental system's hardware consists of laptop computers (NEC Versa-M) with WATMnet interface cards, multiple VME/i960 processor-based WATMnet base stations, and a mobility-enhanced local-area ATM switch. The prototype wireless network interface cards operate at peak bit-rates up to 8 Mb/s, using low-power 2.4 GHz industrial, scientific, and medical (ISM)-band modems. Wireless network protocols at the portable terminal and base station interfaces support available bit rate (ABR), variable bit rate (VBR), and constant bit rate (CBR) transport services compatible with ATM using a dynamic time-division multiple-access/time-division duplex (TDMA/TDD) MAC protocol for channel sharing and data link control (DLC) protocol for error recovery. A custom wireless control protocol is also implemented between the portable and base units for support of radio link related functions such as user registration and handoff. All network entities including the portable, base and switch use a mobility-enhanced version of ATM ("Q.2931+") signaling for switched virtual circuit (SVC) connection control functions, including handoff. In the first stage of the prototype, the application-level API is TCP/UP over ATM ABR service class using AAL5. Early experiments with the WATMnet prototype have been conducted to validate major protocol and software aspects, including DLC, wireless control, and mobility signaling for handoff, Selected network-based multimedia/video applications requiring moderate bit-rates (/spl sim/0.5-1 Mb/s) in the ABR mode have been successfully demonstrated on the laptop PC.

WATMnet: a prototype wireless ATM system for multimedia personal communication

A medium access control (MAC) layer protocol is used in a wireless ATM system for integrated support of ATM services, including constant bit-rate (CBR), variable bit-rate (VBR) and available bit-rate (ABR) services. The MAC protocol supports both connectionless packet and connection-oriented virtual circuit modes, with appropriate service parameter and quality-of-services selection. A dynamic time division, multiple access/time division multiplex (TDMA/TDM) approach accommodates the service classes in an integrated manner. A supervisory MAC procedure integrates ATM ABR/VBR/CBR virtual circuits, providing burst-by-burst allocation of ABR cells and call-by-call allocation of VBR and CBR bandwidth parameters. A mechanism is provided for the dynamic allocation of subframe capacities, assignment of ABR slots based on desired queueing rules, assignment of VBR slots based on ATM traffic shaper parameters and assignment of CBR slots based on bandwidth requirements.

Multiservices medium access control protocol for wireless ATM system

Accurate and timely traffic classification is critical in network security monitoring and traffic engineering. Traditional methods based on port numbers and protocols have proven to be ineffective in terms of dynamic port allocation and packet encapsulation. The signature matching methods, on the other hand, require a known signature set and processing of packet payload, can only handle the signatures of a limited number of IP packets in real-time. A machine learning method based on SVM (supporting vector machine) is proposed in this paper for accurate Internet traffic classification. The method classifies the Internet traffic into broad application categories according to the network flow parameters obtained from the packet headers. An optimized feature set is obtained via multiple classifier selection methods. Experimental results using traffic from campus backbone show that an accuracy of 99.42% is achieved with the regular biased training and testing samples. An accuracy of 97.17% is achieved when un-biased training and testing samples are used with the same feature set. Furthermore, as all the feature parameters are computable from the packet headers, the proposed method is also applicable to encrypted network traffic.

An SVM-based machine learning method for accurate internet traffic classification

The need to quickly and accurately classify Internet traffic for security and QoS control has been increasing significantly with the growing Internet traffic and applications over the past decade. Pattern recognition by learning the features in the training samples to classify the unknown flows is one of the main methods. However, many methods developed in the previous works are too complicated to be applied in real-time, and the prior probabilities based on the training samples are severely biased. This paper uses the SVM (support vector machine) method to train 7 classes of applications of different characteristics, captured from a campus network backbone. A discriminator selection algorithm is developed to obtain the best combination of the features for classification. Our optimized method yields approximately 96.9% accuracy for un-biased training and testing samples. For regular biased samples, the accuracy is about 99.4%. Furthermore, all the feature parameters are computable in real time from captured packet headers, suggesting real time network traffic classification with high accuracy is achievable.

Accurate Classification of the Internet Traffic Based on the SVM Method

This paper proposes a semi-random backoff (SRB) method that enables resource reservation in contention-based wireless LANs. The proposed SRB is fundamentally different from traditional random backoff methods because it provides an easy migration path from random backoffs to deterministic slot assignments. The central idea of the SRB is for the wireless station to set its backoff counter to a deterministic value upon a successful packet transmission. This deterministic value will allow the station to reuse the time-slot in consecutive backoff cycles. When multiple stations with successful packet transmissions reuse their respective time-slots, the collision probability is reduced, and the channel achieves the equivalence of resource reservation. In case of a failed packet transmission, a station will revert to the standard random backoff method and probe for a new available time-slot. The proposed SRB method can be readily applied to both 802.11 DCF and 802.11e EDCA networks with minimum modification to the existing DCF/EDCA implementations. Theoretical analysis and simulation results validate the superior performance of the SRB for small-scale and heavily loaded wireless LANs. When combined with an adaptive mechanism and a persistent backoff process, SRB can also be effective for large-scale and lightly loaded wireless networks.

Ruixi Yuan

Papers

WATMnet: a prototype wireless ATM system for multimedia personal communication

Multiservices medium access control protocol for wireless ATM system

An SVM-based machine learning method for accurate internet traffic classification

Accurate Classification of the Internet Traffic Based on the SVM Method

Semi-random backoff: towards resource reservation for channel access in wireless LANs