Design and Implementation of an Adaptive Feedback Queue Algorithm over Open Flow Networks

The concurrent presence of different types of traffic in multimedia applications might aggravate a burden on the underlying data network, which is bound to affect the transmission quality of the specified traffic. Recently, several proposals for fulfilling the quality of service(QoS) guarantees have been presented. However, they can only support coarse-grained QoS with no guarantee of throughput, jitter, delay or loss rate for different applications. To address these more challenging problems, an adaptive scheduling algorithm for Parallel data Processing with Multiple Feedback(PPMF) queues based on software defined networks(SDN) is proposed in this paper, which can guarantee the quality of service of high priority traffic in multimedia applications. PPMF combines the queue bandwidth feedback mechanism to realise the automatic adjustment of the queue bandwidth according to the priority of the packet and network conditions, which can effectively solve the problem of network congestion that has been experienced by some queues for a long time. Experimental results show PPMF significantly outperforms other existing scheduling approaches in achieving 35--80% improvement on average time delay by adjusting the bandwidth adaptively, thus ensuring the transmission quality of the specified traffic and avoiding effectively network congestion.

TRAFFIC-BASED SCHEDULING MECHANISM IN AN IP/ATM ROUTER

This article briefly presented the design and software architecture of an IP/ATM multiple sub network router. It established the queue model of IP process module and proposed a traffic based scheduling mechanism (AICS: Adaptive Incomplete Cyclic Service). It also provided a simulation study on the system throughput and packet delay jitter performance for both AICS mechanism and IICS mechanism proposed in the prior work. The simulation results show that, comparing with IICS, AICS can provide much better packet delay jitter performance when high speed sub networks exist bursty traffic and give better fairness.

THE NEXT INDUSTRIAL REVOLUTION:INTEGRATED SERVICES AND GOODS

The outputs or products of an economy can be divided into services products ana gooas products （due to manufacturing, construction, agriculture and mining）. To date, the services and goods products have, for the most part, been separately mass produced. However, in contrast to the first and second industrial revolutions which respectively focused on the development and the mass production of goods, the next - or third - industrial revolution is focused on the integration of services and/or goods; it is beginning in this second decade of the 21st Century. The Third Industrial Revolution （TIR） is based on the confluence of three major technological enablers （i.e., big data analytics, adaptive services and digital manufacturing）; they underpin the integration or mass customization of services and/or goods. As detailed in an earlier paper, we regard mass customization as the simultaneous and real-time management of supply and demand chains, based on a taxonomy that can be defined in terms of its underpinning component and management foci. The benefits of real-time mass customization cannot be over-stated as goods and services become indistinguishable and are co-produced - as ＂servgoods＂ - in real-time, resulting in an overwhelming economic advantage to the industrialized countries where the consuming customers are at the same time the co-producing producers.

BIG DATA:UNLEASHING INFORMATION

At present, it is projected that about 4 zettabytes （or 10^＊＊21 bytes） of digital data are being generated per year by everything from underground physics experiments to retail transactions to security cameras to global positioning systems. In the U. S., major research programs are being funded to deal with big data in all five sectors （i.e., services, manufacturing, construction, agriculture and mining） of the economy. Big Data is a term applied to data sets whose size is beyond the ability of available tools to undertake their acquisition, access, analytics and/or application in a reasonable amount of time. Whereas Tien （2003） forewarned about the data rich, information poor （DRIP） problems that have been pervasive since the advent of large-scale data collections or warehouses, the DRIP conundrum has been somewhat mitigated by the Big Data approach which has unleashed information in a manner that can support informed - yet, not necessarily defensible or valid - decisions or choices. Thus, by somewhat overcoming data quality issues with data quantity, data access restrictions with on-demand cloud computing, causative analysis with correlative data analytics, and model-driven with evidence-driven applications, appropriate actions can be undertaken with the obtained information. New acquisition, access, analytics and application technologies are being developed to further Big Data as it is being employed to help resolve the 14 grand challenges （identified by the National Academy of Engineering in 2008）, underpin the 10 breakthrough technologies （compiled by the Massachusetts Institute of Technology in 2013） and support the Third Industrial Revolution of mass customization.

INTERNET OF CONNECTED SERVGOODS:CONSIDERATIONS,CONSEQUENCES AND CONCERNS

In an earlier paper （Tien 2012）, the author augurs that, in contrast to the first and second industrial revolutions which respectively focused on the development and the mass production of goods, the next - or third - industrial revolution is focused on the integration of services and/or goods; it began in this second decade of the 21st Century. The Third Industrial Revolution （TIR） is underpinned by the integration or mass customization of services and/or goods. The benefits of real-time mass customization cannot be over-stated as goods and services become indistinguishable and are co-produced as ＂ServGoods＂, resulting in an overwhelming economic advantage to the industrialized countries where the consuming customers are at the same time the co-producing producers. Adding sensors to these ServGoods and letting them connect or communicate among themselves or with other ServGoods can result in an Intemet of Things （i.e., connected ServGoods）. A number of considerations, consequences and concerns relating to such an Intemet of Connected ServGoods are discussed herein.

Metadata and API Based Environment Aware Content Delivery Architecture

One of the limitations of current content delivery networks is lack of support for environment aware content delivery. This paper first discusses the requirements of such support, and proposes a new metadata gateway based environment aware content delivery architecture. The paper discusses in some details key functions and technologies of environment aware content delivery architecture, including its APIs and control policies. Finally the paper presents an application to illustrate advantages of environment aware content delivery architecture in the context of next generation network.