Semidynamic and dynamic transmission algorithms for multiplexing voice with data

The design of hybrid transmission algorithms for the multiplexing of voice and data over a common digital channel is of interest to various communication networks, including cellular radio and high-speed topologies. In environments where the characteristics of the voice and data traffics may vary dynamically, the issue is the deployment of hybrid multiplexing algorithms (HMAs) which satisfy the constraints imposed by the voice traffic, while they simultaneously attain high channel utilization and induce low implementation overhead. In this paper, we propose, evaluate, and compare two HMAs: a semidynamic and a dynamic. The former induces lower implementation overhead than the latter, but it is applicable only to environments where the rate of the voice traffic may vary relatively slowly and its statistics are parametrically known. The semidynamic HMA induces frame structures, where the capacity allocation per frame, for the voice versus data traffic, is dictated by a superimposed traffic monitoring algorithm. The dynamic HMA, on the other hand, assigns each channel slot to voice versus data packets dynamically; it requires no statistical knowledge about the voice traffic, at the expense of significantly increased implementation overhead.     

Adaptive distributed source coding

We consider distributed source coding in the presence of hidden variables that parameterize the statistical dependence among sources. We derive the Slepian-Wolf bound and devise coding algorithms for a block-candidate model of this problem. The encoder sends, in addition to syndrome bits, a portion of the source to the decoder uncoded as doping bits. The decoder uses the sum-product algorithm to simultaneously recover the source symbols and the hidden statistical dependence variables. We also develop novel techniques based on density evolution (DE) to analyze the coding algorithms. We experimentally confirm that our DE analysis closely approximates practical performance. This result allows us to efficiently optimize parameters of the algorithms. In particular, we show that the system performs close to the Slepian-Wolf bound when an appropriate doping rate is selected. We then apply our coding and analysis techniques to a reduced-reference video quality monitoring system and show a bit rate saving of about 75% compared with fixed-length coding.     

Statistical service assurances for traffic scheduling algorithms

Network services for the most demanding advanced networked applications which require absolute, per-flow service assurances can be deterministic or statistical. By exploiting the statistical properties of traffic, statistical assurances can extract more capacity from a network than deterministic assurances. We consider statistical service assurances for traffic scheduling algorithms. We present functions, so-called effective envelopes, which are, with high certainty, upper bounds of multiplexed traffic. Effective envelopes can be used to obtain bounds on the amount of traffic on a link that can be provisioned with statistical service assurances. We show that our bounds can be applied to a variety of traffic scheduling algorithms. In fact, one can reuse existing admission control functions for scheduling algorithms with deterministic assurances. We present numerical examples which compare the number of flows with statistical assurances that can be admitted with our effective envelope approach to those achieved with existing methods     

Passive Online Detection of 802.11 Traffic Using Sequential Hypothesis Testing with TCP ACK-Pairs

In this paper, we propose two online algorithms to detect 802.11 traffic from packet-header data collected passively at a monitoring point. These algorithms have a number of applications in real-time wireless LAN management, for instance, in detecting unauthorized access points and detecting/predicting performance degradations. Both algorithms use sequential hypothesis tests and exploit fundamental properties of the 802.11 CSMA/CA MAC protocol and the half-duplex nature of wireless channels. They differ in that one requires training sets, while the other does not. We have built a system for online wireless traffic detection using these algorithms and deployed it at a university gateway router. Extensive experiments have demonstrated the effectiveness of our approach: the algorithm that requires training provides rapid detection and is extremely accurate (the detection is mostly within 10 seconds, with very low false-positive and false-negative ratios), the algorithm that does not require training detects 60 percent to 76 percent of the wireless hosts without any false positives, and both algorithms are lightweight, with computation and storage overhead well within the capability of commodity equipment.     

FRR for latency reduction and QoS provisioning in OBS networks

We propose a forward resource reservation (FRR) scheme to reduce the data burst delay at edge nodes in optical burst switching (OBS) systems. We also explore algorithms to implement the various intrinsic features of the FRR scheme. Linear predictive filter (LPF)-based methods are investigated and demonstrated to be effective for dynamic burst-length prediction. An aggressive resource reservation algorithm is proposed to deliver a significant performance improvement with controllable bandwidth cost. By reserving resources in an aggressive manner, an FRR system can reduce both the signaling retransmission probability and the bandwidth wastage as compared with a system without the aggressive reservation. An FRR-based QoS strategy is also proposed to achieve burst delay differentiation for different classes of traffic. Theoretical analysis and simulation results verify the feasibility of the proposed algorithms and show that our FRR scheme yields a significant delay reduction for time-critical traffic without incurring a deleterious bandwidth overhead.     

A fast lightweight approach to origin-destination IP traffic estimation using partial measurements

In this paper, a novel approach is proposed for estimating traffic matrices. Our method, called PamTram for PArtial Measurement of TRAffic Matrices, couples lightweight origin-destination (OD) flow measurements along with a computationally lightweight algorithm for producing OD estimates. The first key aspect of our method is to actively select a small number of informative OD flows to measure in each estimation interval. To avoid the heavy computation of optimal selection, we use intuition from game theory to develop randomized selection rules, with the goals of reducing errors and adapting to traffic changes. We show that it is sufficient to measure only one flow per measurement period to drastically reduce errors-thus rendering our method lightweight in terms of measurement overhead. The second key aspect is an explanation and proof that an Iterative Proportional Fitting algorithm approximates traffic matrix estimates when the goal is a minimum mean-squared error; this makes our method lightweight in terms of computation overhead. A one-step error bound is provided for PamTram that bounds the average error for the worst scenario. We validate our method using data from Sprint's European Tier-1 IP backbone network and demonstrate its consistent improvement over previous methods.     

DraLCD:一种新的数据中心流量工程方法

流量均衡是为了避免网络拥塞而作为流量工程中的路由优化目标提出来的,由于数据中心网络的流量特性,使得传统IP网络的流量工程方法不一定适合.为此,本文在SDN(Software Defined Network)的框架下,提出了一种基于链路关键度的自适应负载均衡流量工程方法:DraLCD(Dynamic Routing Algorithm based on Link Critical Degree).该方法通过对全局视图的网络管控,并充分利用了网络中存在的冗余路径,在完成细粒度流量均衡的同时,能够降低控制器的计算开销以及与交换机之间的通信开销,最终完成路由优化的目标.最后,基于DraLCD设计的原型系统,通过在Mininet仿真平台中部署并进行仿真实验,与现有的等开销多路径路由算法ECMP(Equal-Cost Multi-Path)以及GFF(Global First Fit)路由算法相比较,能够明显地提升网络性能.     

Efficient Power‐Saving 10‐Gb/s ONU Using Uplink Usage‐Dependent Sleep Mode Control Algorithm in WDM‐PON

We propose and demonstrate an efficient power‐saving optical network unit (ONU) based on upstream traffic monitoring for 10‐Gb/s wavelength division multiplexed passive optical networks (WDM‐PONs). The power‐saving mode controller uses a μ‐processor and traffic monitoring modules followed by the proposed power‐saving processes to operate the sleep mode ONU. The power consumption of the ONU is effectively reduced from 19.3 W to 6.4 W when no traffic from the users is detected. In addition, we design a power‐saving mechanism based on a cyclic sleep mode operation to allow a connectivity check between the optical line terminal and ONU. Our calculation results show that the WDM‐PON ONU reduces the power consumption by around 60% using the proposed mechanism.     

Energy-Efficient Map Interpolation for Sensor Fields Using Kriging

We propose a spatial autocorrelation aware, energy efficient, and error bounded framework for interpolating maps from sensor fields. Specifically, we propose an iterative reporting framework that utilizes spatial interpolation models to reduce communication costs and enforce error control. The framework employs a simple and low overhead in-network coordination among sensors for selecting reporting sensors so that the coordination overhead does not eclipse the communication savings. Due to the probabilistic nature of the first round reporting, the framework is less sensitive to sensor failures and guarantees an error bound for all functional sensors for each epoch. We then propose a graceful integration of temporal data suppression models with our framework. This allows an adaptive utilization of spatial or temporal autocorrelation based on whichever is stronger in different regions of the sensor field. We conducted extensive experiments using data from a real-world sensor network deployment and a large Asian temperature dataset to show that the proposed framework significantly reduces messaging costs and is more resilient to sensor failures. We also implemented our proposed algorithms on a sensor network of MICAz motes. The results show that our algorithms save significant energy and the out of bound errors due to packet loss are below 5%.     

Statistical methods to estimate vehicle count using traffic cameras

Traffic camera has played an important role in enabling intelligent and real-time traffic monitoring and control. In this paper, we focus on establishing a correlation model for the traffic cameras’ vehicle counts and increase the spatial-resolution of a city’s vehicle counting traffic camera system by means of correlation-based estimation. We have developed two methods for constructing traffic models, one using statistical machine learning based on Gaussian models and the other using analytical derivation from the origin-destination (OD) matrix. The Gaussian-based method outperforms existing correlation coefficient based methods. When training data are not available, our analytical method based on OD matrix can still perform well. When there is only a limited number of cameras, we develop heuristic algorithms to determine the most desirable locations to place the cameras so that the errors of traffic estimations at the locations without traffic cameras are minimized. We show some improvements in the performance of our proposed methods over an existing method in a variety of simulations.

分布式并行数据挖掘计算框架及其算法研究

为了提供一个灵活可扩展的计算平台进行高效的挖掘计算，提出了一种应用于分布和并行环境的数据挖掘计算框架和相应的算法。通过分析关联规则挖掘理论和以往算法的优缺点，建立一种分布式并行数据挖掘的计算框架，并给出相应的求解算法。实例分析表明该计算框架能够减少节点问的通信开销，保持了良好的可扩展性：挖掘算法则利用本地节点动态有序集合枚举树生成方法代替数据库节省了本地空间的占用．大大提高了查找的计算效率。     

Real-time mixed-traffic wireless networks

In this paper we introduce a new protocol, prioritized carrier sense multiple access with collision avoidance, for real-time wireless local area networking. Wireless networks increasingly will be called upon to carry mixed traffic, some portion of which will be devoted to real-time control and monitoring. Our protocol, based upon the IEEE 802.11 wireless standard, mixes real-time traffic with standard multimedia data in a way which assures loop stability. Scheduling the real-time traffic is the primary issue considered. Under our framework, we propose and validate several new algorithms for dynamically scheduling the traffic of wireless networked control systems: constant penalty, estimated error order and lag first-order schemes. All algorithms are compared via simulation and the results show that dynamic scheduling algorithms achieve better system performance on average than static scheduling algorithms like fixed-order polling. The results of a real experiment involving two dryer plants and three IEEE 802.11 nodes are reported with static scheduling employed as it lower bounds the closed-loop behavior     

Distributed fault-tolerant channel allocation for cellular networks

A channel allocation algorithm includes channel acquisition and channel selection algorithms. Most of the previous work concentrates on the channel selection algorithm since early channel acquisition algorithms are centralized and rely on a mobile switching center (MSC) to accomplish channel acquisition. Distributed channel acquisition algorithms have received considerable attention due to their high reliability and scalability. However, in these algorithms, a borrower needs to consult with its interference neighbors in order to borrow a channel. Thus, the borrower fails to borrow channels when it cannot communicate with any interference neighbor. In real-life networks, under heavy traffic load, a cell has a large probability to experience an intermittent network congestion or even a communication link failure. In existing distributed algorithms, since a cell has to consult with a large number of interference neighbors to borrow a channel, the failure rate will be much higher under heavy traffic load. Therefore, previous distributed channel allocation algorithms are not suitable for real-life networks. We first propose a fault-tolerant channel acquisition algorithm which tolerates communication link failures and node (MH or MSS) failures. Then, we present a channel selection algorithm and integrate it into the distributed acquisition algorithm. Detailed simulation experiments are carried out in order to evaluate our proposed methodology. Simulation results show that our algorithm significantly reduces the failure rate under network congestion, communication link failures, and node failures compared to nonfault-tolerant channel allocation algorithms. Moreover, our algorithm has low message overhead compared to known distributed channel allocation algorithms, and outperforms them in terms of failure rate under uniform as well as nonuniform traffic distribution     

Dynamic load balancing in WDM packet networks with and without wavelength constraints

We develop load balancing algorithms for WDM-based packet networks where the average traffic between nodes is dynamically changing. In WDM-based packet networks, routers are connected to each other using wavelengths (lightpaths) to form a logical network topology. The logical topology may be reconfigured by rearranging the lightpaths connecting the routers. Our algorithms reconfigure the logical topology to minimize the maximum link load. In this paper, we develop iterative reconfiguration algorithms for load balancing that track rapid changes in the traffic pattern. At each reconfiguration step, our algorithms make only a small change to the network topology hence minimizing the disruption to the network. We study the performance of our algorithms under several dynamic traffic scenarios and show that our algorithms perform near optimally. We further show that these large reconfiguration gains are achievable in systems with a limited number of wavelengths.     

Minimum-energy multicast in wireless ad hoc networks with adaptive antennas: MILP formulations and heuristic algorithms

In this paper, we consider wireless ad hoc networks that use adaptive antennas and have limited energy resources. To explore the advantages of power saving offered by the use of adaptive antennas, we consider the case of source initiated multicast traffic. We present a constraint formulation for the MEM (Minimum-Energy Multicast) problem in terms of MILP (Mixed Integer Linear Programming) for wireless ad hoc networks. An optimal solution to the MEM problem using our MILP model can always be obtained in a timely manner for moderately sized networks. In addition to the theoretical effort, we also present two polynomial-time heuristic algorithms called RB-MIDP and D-MIDP to handle larger networks for which the MILP model may not be computationally efficient. The experimental results show that our algorithms compare well with other proposals discussed in this paper.     

An Application Oriented Power Saving MAC Protocol for Wireless Sensor Networks

Energy efficiency has been an important concern in wireless sensor networks where Medium Access Control (MAC) protocol plays an important role. However, current MAC protocols designed for energy saving have seldom considered multiple applications coexisting in WSN with variation of traffic load dynamics. In this paper, we propose an adaptive control algorithm at MAC layer to promote energy efficiency. We focus on the tradeoff relation between collisions and control overhead as a reflection of traffic load and propose to balance the tradeoff under the constraints of QoS options. We integrate the algorithm into S-MAC and verify it through NS-2 platform. The simulation results demonstrate that our algorithm achieves observable improvement in energy performance while meeting QoS requirement for different coexisting applications in comparison with S-MAC.     

AdaptiveMutate: a technique for privacy preservation

Mobile apps are known to be rich sources for gathering privacy-sensitive information about smartphone users. Despite the presence of encryption, passive network adversaries who have access to the network infrastructure can eavesdrop on the traffic and therefore fingerprint a user’s app by means of packet-level traffic analysis. Since it is difficult to prevent the adversaries from accessing the network, providing secrecy in hostile environments becomes a serious concern.In this study, we propose AdaptiveMutate, a privacy-leak thwarting technique to defend against the statistical traffic analysis of apps. First, we present a method for the identification of mobile apps using traffic analysis. Further, we propose a confusion system in which we obfuscate packet lengths, and/or inter-arrival time information leaked by the mobile traffic to make it hard for intruders to differentiate between the altered app traffic and the actual one using statistical analysis. Our aim is to shape one class of app traffic to obscure its features with the minimum overhead. Our system strives to dynamically maximize its efficiency by matching each app with the corresponding most dissimilar app. Also, AdaptiveMutate has an adaptive capability that allows it to choose the most suitable feature to mutate, depending on the type of apps analyzed and the classifier used, if known.We evaluate the efficiency of our model by conducting a comprehensive simulation analysis that mutates different apps to each other using AdaptiveMutate. We conclude that our algorithm is most efficient when we mutate a feature of one app to its most dissimilar one in another app. When applying the identification technique, we achieve a classification accuracy of 91.1%. Then, using our obfuscation technique, we are able to reduce this accuracy to 7%. Also, we test our algorithm against a recently published approach for mobile apps classification and we are able to reduce its accuracy from 94.8% to 17.9%. Additionally, we analyze the tradeoff between the shaping cost and traffic privacy protection, specifically, the associated overhead and the feasibility for real-time implementation.     

Battery-aware Routing in Personal Networks

A personal network (PN) is a network of devices belonging to a person. It can consist of a number of ad hoc sub-networks which are linked together through the Internet. We study battery-aware routing for multi-hop connectivity in sub-networks of PNs, and propose a new algorithm. The proposed algorithm takes the advantage of having mains-connected devices in a PN to direct the traffic to such devices and avoid relaying over nodes with low battery energy. A consequence of this strategy is directing the traffic load to static nodes of the network as well, since mains-connected nodes are static while battery-powered nodes could be mobile. This results in less route failures due to less mobility of nodes along a chosen path. We comprehensively compare the performance of our proposed algorithm with the performance of some well-known algorithms from the literature. We consider the effect of node density, routing overhead, heterogeneity of nodes in terms of their power supplies, gateway-oriented communication, mobility of nodes, and transmission power control, on the performance of battery-aware routing algorithms in PNs. Taking into account various parameters and different scenarios, we show that directing the traffic to mains-powered nodes can profoundly increase operational lifetime of the network. Our algorithm, as well as the results of our work, can also be applied to other types of ad hoc networks with heterogeneous power supplies.     

面向可扩展的VANETs混合路由的研究与仿真

车载网VANETs(Vehicular ad hoc networks)属于高速移动的无线网络,可供车辆安全、交通监测以及其他的商业服务的应用。然而,为此,提出混合式的位VANETs中车辆的快速移动导致通信链路频繁地断裂,增加路由开销,降低了可扩展性。议地理位置路由的特点。HLAR(Hybrid location-based ad hoc routing)。HLAR结合了反应式路由、HLAR克服了反应式路由的扩展性问题,并改善了地理位置路由对位置误差的敏感性。同时,通过理论分析,量可扩展性,并推导了路由开销的表达式。通过分析、仿真表明,提出的路由协议具有很好的扩展性,并降低了路由开销。在仿真中引入位置误差因子,结果表明。同时,与同类的其他协议相比,输时延方面HLAR到对位置误差具有很强的鲁棒性HLAR在数据传输率、端到端传提升。     

Analyzing Control Traffic Overhead versus Mobility and Data Traffic Activity in Mobile Ad-Hoc Network Protocols

This paper proposes a general, parameterized model for analyzing protocol control overhead in mobile ad-hoc networks. A probabilistic model for the network topology and the data traffic is proposed in order to estimate overhead due to control packets of routing protocols. Our analytical model is validated by comparisons with simulations, both taken from literature and made specifically for this paper. For example, our model predicts linearity of control overhead with regard to mobility as observed in existing simulations results. We identify the model parameters for protocols like AODV, DSR and OLSR. Our model then allows accurate predictions of which protocol will yield the lowest overhead depending on the node mobility and traffic activity pattern.