Shear wave elastography (SWE) is a quantitative imaging method that could be used for clinical assessment of musculoskeletal stiffness, particularly in disease diagnosis and rehabilitation evaluation. However, the elastic anisotropy of skeletal muscle leads to uncertainties in shear wave velocity (SWV) measurements in SWE because the SWV varies with muscle fiber orientation. Therefore, many studies have conducted 360° rotational measurements of SWV to determine the elastic anisotropy of muscle; however, the extended data acquisition time of this approach limits its clinical utility. In this study, a T-shaped transducer was used for rapidly measuring the longitudinal and transverse SWVs ( $\textit {SWV}_{L}$ and $\textit {SWV}_{T}$ ) of muscle through an ellipse fitting method to estimate the fiber orientation angle when the excitation is normal to the material axis. The performance of this approach was examined by conducting a homogeneous elastic phantom experiment, which indicated that the proposed T-shaped transducer generated shear waves in three directions by applying a supersonic push at the junction of the transducer. The error between the measured SWVs and ground truth was approximately 6.5%. The proposed T-shaped transducer was also used to measure the SWV in the biceps brachii of four healthy individuals. The $\textit {SWV}_{L}$ and $\textit {SWV}_{T}$ values measured with this transducer were 2.47 and 1.09 m/s, respectively, which were consistent with the SWVs obtained under 360° rotation and in the literature (an error of ~4%). All experimental results were consistent with the results obtained under 360° rotation, which indicates that the proposed method enables the rapid and stable estimation of muscle fiber orientation in SWE.

We design and implement a 3GPP Rl6-compliant data plane for 5G networks to support Time Sensitive Networks (TSN) in bridge mode based on free5GC and UERANSIM, two open-source projects. We address the concerns of time synchronization in 5G systems, the interaction between the 5G TSN bridge and the TSN control plane, maintenance of TSN capabilities by the 5G TSN bridge, and clock drift of the 5G TSN bridge. Through experiments, the accuracy of a 5G TSN bridge with the proposed time synchronization capability is demonstrated to be 13 times better than that of one without this capability. Furthermore, we analyze the performance of the topology establishment functionality provided by the 5G TSN bridge and show that the impact of clock drift can be reduced by implementing clock drift reporting in the 5G TSN bridge. Finally, we present a solution to implement a 5G system data plane to support TSN and provide an open platform for further extensions and improvements based on the results of this work, which can be used to continue the development of relevant features for 3GPP R17 and RlS.

This paper details the development of an ultra-broadband Low Noise Amplifier (LNA) tailored for Beyond 5G (B5G) and 6th Generation (6G) applications. The innovative design of the LNA comprises a three-stage differential common-source (CS) topology, augmented with neutralization capacitors to substantially improve both stability and gain. The circuit's input stage integrates a balun, inductors, and capacitors to ensure wideband gain optimization. Furthermore, transformer matching is employed for inter-stage connections to achieve the goal of a wideband low-noise amplifier.The LNA is fabricated using a 28-nm CMOS process and is operational across the entire W-band, spanning a frequency range of 70 to 110 GHz. This corresponds to a fractional bandwidth of 44.44%. The device achieves a minimum noise figure of 6.1 dB at 81 GHz and sustains an average noise figure of 7.5 dB across the bandwidth. Additionally, the LNA delivers an average gain of 12.5 dB while consuming 60 mW of DC power. The total area of the circuit is 0.53 mm2.

As the number of connected devices continues to increase and the complexity of services supported by 5G grows, significant challenges may arise in managing the important signaling and processing of the control plane. This will result in extensive resource utilization. While deploying additional resources may be relatively straightforward, the decision-making process for resource scaling poses a challenge. Hence, this paper provides the 5G network management system with the capability of system load prediction to assist in the decision-making process of resource scaling. To apply system load prediction to the 5G core (5GC) network, we collect real-time performance measurement data from the 5GC network using open-source 5G software. We utilize this data to train neural networks to predict the load of 5GC network functions. Additionally, we design a specific loss function for the prediction model to align with our resource scaling strategy objectives. Experimental results demonstrate that the application of performance measurements enhances the accuracy of load prediction tasks, thereby contributing to more effective resource management.

Datacenter applications demand a fast response time for short messages to enhance the user experience. Therefore, optimizing the flow completion time (FCT) for short flows is a primary objective for data center networks. Multilevel feedback queue (MLFQ) scheduling has been a widely used algorithm for process scheduling. In this paper, we propose an approximate MLFQ (AMFQ) scheduling algorithm that runs on programmable switches at line rate for data center networks. AMFQ separates incoming network traffic into multiple priority queues, ensuring low queueing delays for short flows. AMFQ adapts the time quantum concept of MLFQ. The number of time quantum will increase proportionally, while the priority of the queue decreases. The number of quantums will decide how long the packets of the flow will be served in the queue. However, implementing AMFQ using a programmable switch with millions of timers to attach to millions of flows is not feasible. Therefore, we propose to group a set of flows to form a version to be scheduled together using only one timer. We evaluated the performance of AMFQ on a P4-based testbed and compared it with existing solutions. The results show that AMFQ achieves better performance while reducing FCT for short flows, making it a promising solution for high-speed data center networks.

Datacenter applications desire low latency for short messages to provide a better user experience. Therefore, one of the goals of datacenter networks is to minimize flow completion time (FCT), especially for short flows. Multiple scheduling disciplines have been proposed to achieve this goal. In this paper, we develop Dynamic Longer Stay Less Priority (D-LSLP) which looks at the current queue occupancy to adjust the demotion threshold for the packets of the flows arriving in the strict priority queues. Initially, D-LSLP considers every flow to be a short flow, and with the passage of time, the flow is demoted to the next priority queue, similar to MLFQ. We leverage the programmable nature of the P4 switches and measure the instant queue occupancy in the P4 to automatically adjust the demotion threshold only for the highest priority queue. This enables DLSLP to increase or decrease its highest priority demotion threshold based on the instant queue status. It enables short flows to complete in a couple of higher-priority queues. In contrast, large flows are demoted to lower priority queues after remaining active in the queues for a certain amount of time. D-LSLP allows multiple traffic patterns to coexist without the need to manually tune the demotion thresholds. Furthermore, it helps reduce tail drop in the highest priority queue when it is overwhelmed by many short flows. The performance evaluation shows that it works well with different traffic patterns without operator intervention.

In order to provide an industry-grade 5G Private Network (PN) to the enterprises, the ultra-reliability communication becomes a key feature to successfully deploy 5G PNs for the future industry 4.0 applications. This paper article will use the free5GC, which is the world's first open-source 5G core (5GC) network that complies with 3rd Generation Partnership Project (3GPP) R15 standards, developed in the laboratory as the base to develop a redundant transmission technique for Ultra-Reliable Communication in 5G Core Networks. We compare the its performance and reliability with the original a single protocol data unit (PDU) session in free5GC. Moreover, it confirmed that the reliability it brings would enable users to have a better user experience.

The goal of P4MT is to leverage the role-based control mechanism in P4Runtime Specification to further enable multi-tenancy on a single P4 switch. The evaluation results show that P4MT consumes only a small percentage of ASIC space and causes a negligible increment in data plane/control plane latency. International P4 Experimental Networks (i-P4EN) has been created to realize the potential of P4 experimental networks. To perform multiple experiments for research groups, multitenancy is required to increase the efficiency of the testbed. By modifying the P4Runtime design and P4 pipeline, we designed and implemented multi-tenancy on a P4 switch. With P4MT, each tenant can select its own P4 pipeline and control the packet processing without intervening with the packet processing of other tenants. Future work includes supporting P4 Externs for programmable data plane networking, multi-tenant networking and automatic pipeline migration on P4MT.

The Virtual Customer Premises Equipment (vCPE) technology has recently emerged to reduce telecom operators' OPEX and CAPEX. It evolved from Network Function Virtualization (NFV) and Software Defined Networking (SDN) technologies. This paper proposes a flexible vCPE framework to enable dynamic chaining of Virtual Network Functions (VNF) by using Programmable Protocol-independent Packet Processors (P4) switches. It can obtain a much better packet processing performance compared to the pure software vCPE solution. The OpenFlow switch provides similar hardware acceleration, but it executes the flow tables in a fixed order, and it is not possible to skip the flow tables, which are not subscribed to by a customer. However, P4, the domain-specific language used to describe how to process packets on a data plane (DP), gives more flexibility than the OpenFlow. It provides a way to avoid the fixed flow table execution order and can introduce a new service on the fly. Our flexible vCPE framework can be achieved by the synergies between an NFV controller on the cloud and a P4 switch at the edge. In this paper, an Open Network Operating System (ONOS) controller with P4Runtime is used as a VNF control plane and a P4 Behavioral Model (BMv2) software switch is used as a DP. Finally, dynamic function chaining is realized using three possible implementations, viz. multi-instance, clone, and resubmit. P4 language is used for the implementations. Experimental results show that a multi-instance based solution is better than a resubmit and clone.

In 5G, the requirement of transmission latency is stricter than that in 4G. To enhance transmission efficiency, a user plane function (UPF) with a specific packet processing mechanism is necessary. However, UPF must communicate with the session management function (SMF), which will send the packet processing rules to UPF. Those rules will substantially occupy UPF storage. Moreover, customizing a UPF needs to reconstruct N3, N4, N6, and N9 interfaces, which takes much time for developers. To this end, we propose the user plane function development framework (UPFDF), which modularizes the functions in the UPF, supporting customization to connect different types of packet processing mechanisms. With UPFDF, we address the UPF capacity problem and improve the flexibility of the system.

The Quality of Service (QoS) for applications is becoming increasingly important with the expansion of the Internet. A software-defined network offers flexibility and scalability in the use of network resources, like a meter table, which enables OpenFlow switches to measure flow rates and can be used to realize the rate limiter QoS. However, this drops packets when the flow-rate is over the limit, making the TCP congestion window reduce and grow periodically. The QoS of the upper layer using TCP will suffer regularly because of packet losses and bandwidth oscillation. Therefore, we propose a QoSTCP protocol using the meter and Rate Limiting Notification (RLN) to improve the QoS of TCP in SDN. The meter in the switch measures the flow rate to mark RLNs in the packets when the flow rate exceeds the threshold. A QoSTCP sender gets marking information to reduce the window size proportional to the marking packet ratio to avoid packet drop. We also provide a theoretical analysis to estimate when to mark packets at specific thresholds under two kinds of bandwidth demands in QoS, maximum and average rate. In order to verify QoSTCP performance, we implement a Two Rate Three Color Marker (trTCM) meter to measure the flow rate and mark RLNs using a Programming protocol-independent Packet Processors (P4) switch. To simplify our implementation, the existing Explicit Congestion Notification (ECN) and Data Center TCP (DCTCP) are modified to emulate QoSTCP behavior. Experiment results confirm not only that QoSTCP provides a consistent rate guarantee by avoiding packet drop but also that it matches our theoretical analytical results.

In Internet of Things (IoT) environment, devices often do not have public IPs to communicate with other devices due to addresses getting exhausted. Therefore, Network Address Translation (NAT) is used to translate IPs. Furthermore, NATs often also filter messages just like firewalls, and different types of NATs have different behavior on filtering. This causes difficulties for devices direct communication. However, although there are some NAT traversal methods can be used to traverse NATs, those methods may produce extra overhead or require need to distinguish the types of NATs at first. In this paper, an SDN-based NAT traversal mechanism is proposed to deal with the NAT traversal problem without previous mentioned problems. The centralized management property of software-defined networking (SDN) is utilized to develop this SDN-based NAT traversal mechanism. The functions of NATs are implemented on the controller as an NAT application. The controller controls the translating of addresses and ports, so the controller can own all information to traverse all kinds of NATs. From simulation results, the proposed NAT traversal method can successfully use the same process to traverse all kinds of NATs without producing extra overhead. Furthermore, the NATs are OpenFlow switches in the data plane, so it is flexible to adjust the settings of NATs.

In order to accomplish a stringent speed requirement for processing internet services such as Access Control List (ACL), Quality of Service (QoS), firewalls, etc., software based OpenFlow switches must have a fast packet classification capability. Even for hardware based OpenFlow switches, a limited size of Ternary Content Addressable Memory (TCAM) in the switch could be only enough for a forwarding table. Therefore, ACL, firewall tables, etc. need to be implemented by using the memory of the switch CPU. However, it has become a great challenge to build extremely effectively for next-generation software based packet classification that supports higher throughput and larger flow entries in OpenFlow switch. This paper first exploits a fast packet classification algorithm that forms a R*-Tree based Bitmap Intersection and secondly discusses an enhanced R*-Tree based Bitmap Intersection by using Bloom Filter and Multiple R*-Tree. The evaluation results show that the performance of the algorithm in OpenFlow switches is 4.42 times of Bitmap Intersection and 5.16 times of R*-Tree algorithm and consumes only 300 KB of memory space, which is much less than that of other methods. Finally, the use of multiple R*-Trees has further improved memory usage by about 30%.

We present the first Media-Aware Network Element (MANE) for intelligently streaming scalable video sequences in P4 programming language. Our MANE selectively drops queued scalable video packets when the queue occupancy exceeds a threshold. Three packet discarding logics are implemented: (i) tail, (ii) enhancement-layer, and (iii) rate-distortion optimized. Our P4-based MANE implementation is demonstrated in: (i) larger emulated networks in mininet with P4 software switches and (ii) a small real network with a physical P4 switch and multiple Raspberry Pis running P4 software switches.

In order to check a membership in multiple sets of bloom filter in a dynamic bloom filter, a sequential search is usually used. Since the distribution of queried data is unpredictable because the distribution has a feature of temporal locality. Therefore more search cost is incurred if queried data is stored in the peer which is corresponded to the Bloom Filter has lower query priority. In this paper, we introduce Dynamic Reordering Bloom Filter that can save the cost of searching Bloom Filter by dynamically reorder the searching sequence of multiple bloom filters in a dynamic bloom filter with One Memory Access Bloom Filter (OMABF) and checked in the order saved in Query Index (QI). The performance of the system is evaluated by Markov Chain. Simulation results show that our scheme on average has 43% better in searching performance comparing with the sequential methods, which is verified via three different trace log files.

Despite being industry standard, load balancing via virtual machine (VM) migration methods in modern cloud data centers still exhibit two major performance issues: resulting system load balancing degree and total time till balanced state. Over the years research has been conducted to improve these metrics. Yet due to the fact that these issues influence each other, it has been a challenge to achieve substantial advancement in both metrics simultaneously. In this paper we study the problem of VM migration with load balancing and migration time constraints. We formulate this problem as a variation of multi-commodity minimum cost flow problem and show how both resulting degree of imbalance and a total migration time can be optimized together. We also propose a heuristic method based on Ant Colony Optimization family of algorithms. Through simulation results we show that our heuristic gives good performance results compared to optimal solutions to minimum cost flow problem. Furthermore, our method achieves on average twice faster migration time compared to existing methods, proposed in related works.

Network function virtualization (NFV) has drawn much attention in recent years, where some network functions that used to be deployed on specific hardware have become virtualized instances on general servers to achieve more scalability and flexibility. In a data center, service function chaining (SFC) makes a workflow traverse different network functions in a specific order to provide different levels of service for its customer. Because the distance between any adjacent network functions in a service chain will decide the total bandwidth consumption for that chain, the placement of the virtualized network functions in a data center becomes an important problem. In this study, this placement problem is treated as a multi-layer bin packing problem. Two greedy algorithms are proposed for the tree-like network topology: Multi-layer Worst-Fit (MWF) and Multilayer Best Fit (MBF). Furthermore, the placement problem is formulated as an integer linear programming. The experimental results show that MWF can reduce bandwidth consumption by 15% while only increasing the number of used servers by 1% compared to the traditional Best-fit algorithm.

Compared with current distributed networks, Software defined networking is an innovative technology to manage networks by a centralized controller with global visibility. OpenFlow is one kind of SDN protocols. It provides flow-level controllability of network traffic to simplify the management of the administrators of data center. Flow control rules used by OpenFlow in switch flow table are called flow entries. Modern commodity switches use TCAM to implement flow table because of its high matching speed. However, the general TCAM size of switch only accommodates up to thousands of flow entries due to its high cost-to-density ratio and high power consumption. It indicates that the maximal number of flow that can be controlled is restricted to the TCAM size of switch. That leads to several scalability issues, especially in a data center. In this paper, we propose a topology based flow entry management (TFEM) technique, which is a scalable and memory-efficient solution by exploiting the hierarchical topology characteristic to aggregate the uses of flow entries for most of the small flows in a data center. With the proposed downlink and uplink separated flow tables structure, our results show that TFEM can reduce the average number of flow entries by 50%~78% for fat-tree topology against the traditional SDN without any switch hardware modification.

Multipath routing in data center has been studied intensively in recent years in order to minimize the finish time of data transfer or the latency of message sending. Existing scheme of splitting traffic at the granularity of packets can cause reordered packets within a TCP flow. Another alternative scheme of splitting traffic at the granularity of a flow avoids packet reordering but may increase latency as it does not differentiate between elephant and mice flows. A newer efficient approach is to split elephants down into many mice flows, and distribute them uniformly at random over all paths. However, elephant detection is mandatory and the performance is largely depends on accuracy of the elephant detection. We propose, a simple yet effective multipath routing that leverage the same idea of splitting elephants down into many mice flows but without any farther requirement of elephant flow detection by using the hard time-out based flow removal feature of OpenFlow switches. Furthermore, we integrate a VLAN based routing scheme to addresses the challenges of cost-effective scalability. As per our simulation using mininet, we found a 44% reduction in overall flow completion time (FCT) compared to TinyFlow and 32% reduction in the consumption of flow table entry resources inside of aggregate switches in datacenter.

The Internet has evolved greatly in this decade. For economic benefits, the management of Internet networks needs to adapt to mass changes without huge modifications in hardware and software. Especially in campus networks, there are a variety of users and devices with different Quality of Service (QoS) requirements and management policies. Software-defined networking (SDN) decouples the data and control planes. The separated control plan resides on a centralized controller to make networks easier to manage. In this paper, a role-based SDN campus network slicing is proposed by utilizing an authentication controller and the virtualization technology of FlowVisor to divide the campus network into several virtual networks according to the types of users. However, the mapping between the devices' MAC addresses and the users' roles results in a heavy loading problem on FlowVisor. Therefore, a VLAN-based slicing is introduced in this framework to offload the workload of FlowVisor for classifying packets into corresponding slices. Packets are appended with VLAN tags for recognizing types of users to lower the overhead of FlowVisor. Analyses of experimental results show that compared with MAC-based slicing, VLAN-based slicing can reduce the flow setup latency by 14% to 60% depending on the number of devices.

In the common implementation of software defined networking where only one controller is used, tasks required by various applications may overwhelm the controller as the network grows, leading to degradation of the network performance. Some multi-controller architectures have been proposed to remedy such scalability issue. In this paper, we present our design and implementation of a routing application under a hierarchical multi-controller architecture. In this architecture, a network is partitioned into multiple domains, each of which is managed by a dedicated local controller, which is managed by a common global controller. The routing application is executed on the local and global controllers, jointly providing a routing service for each new flow. We provide effective mechanisms to reduce the link state that should be kept by the global controller. We propose a weight function on the links so that a weighted shortest path can be found that avoids the congested links on the network. Experiments results show that our routing application in the hierarchical multi-controller architecture has a great improvement over that of the single-controller architecture in terms various performance metrics.

This paper proposes a Software Defined Network (SDN) architecture for GeoBroadcast in VANETs. We have implemented a component to automatically manage the geographical location of Road Side Units (RSUs), which are used as a basis for our GeoBroadcast routing. GeoBroadcast in a vehicular network supports periodic broadcast messages from a source vehicle to the destination vehicles that are located in a specific geographical region. In existing Intelligent Transport Systems (ITS), the GeoBroadcast mechanism can be implemented using traditional IP networking. Typically, every periodic warning messages received at nearest RSU from the source must be routed to the control center in ITS, where it is redirected to every other RSUs, that are located in the destination geographical region for broadcasting. As a result, huge overhead in the control center is produced and higher network bandwidth is consumed. However, in our SDN based GeoBroadcast mechanism, the first warning message received by the source RSU is sent to the SDN controller as a packet-in message. The SDN controller will decode the packet-in message and use topological and geographical information to set up the routing paths to the destination RSUs, by installing appropriate flow entries on the corresponding RSUs and intermediate switches, for the following periodic warning messages that are to be broadcasted. As per our simulation with OpenNet a significant reduction by 84% in controller overhead, 60% in network bandwidth consumption, and 81% in latency are achieved.

This paper focuses on channel assignment in wireless mesh networks. Since nodes have only a limited number of radio interfaces, channel assignment must ensure that the interface constraint is obeyed. Although many channel assignment heuristics have been proposed, the interface constraint is usually treated as a separate constraint that is not well incorporated in the heuristics themselves. In this paper, we propose a mixed hypergraph model that captures the interface constraint on nodes and the interference between links. We propose a greedy-based channel assignment algorithm that minimizes the interference between links while conforming to the interface constraint. Simulation results show that our proposed algorithm performs especially well when the number of network interface cards is small.

This paper proposes an effective elephant flow detection in datacenters. Equal Cost MultiPath (ECMP) is a popular routing mechanism to achieve load balancing in datacenter networks. However, ECMP only considers equally distributing the flows over equal-length paths, but does not take the size of the flows into account. Previous studies show that detecting and rerouting elephant flows (flows that transfer significant amount of data) effectively can lead to a 113% improvement in aggregate throughput compared with the simple use of ECMP. A naive way to detect the elephant flows is to pull statistics from each flow independently. Since "the elephant and mouse phenomenon" suggests that there are only very few elephant flows in a datacenter network, it's not efficient to collect information from each flow. Therefore, we propose a Hierarchical Statistics Pulling (HSP) mechanism using OpenFlow protocol to save bandwidth consumption and processing time. In order to further improve the performance of HSP, two supplement functions called elephant store and range splitting are developed. Our approaches can detect elephant flows with only a small amount of network bandwidth consumption. We use Mininet emulator and mathematical analysis to verify our methods. Both of them confirm the benefits of our approaches.

It becomes a challenge to design an efficient load balancing method via live virtual machine (VM) migration without degrading application performance. Two major performance impacts on hosted applications that run on a VM are the system load balancing degree and the total time till a balanced state is reached. Existing load balancing methods usually ignore the VM migration time overhead. In contrast to sequential migration-based load balancing, this paper proposes using a network-topology aware parallel migration to speed up the load balancing process in a data center. We transform the VM migration-based multi-resource load-balancing problem into a minimum weighted matching problem over a weighted bipartite graph. By obtaining the minimum weighted matching pairs through the Hungarian method, we parallel migrate multiple VMs from overloaded hosts to underutilized hosts to reduce the time it takes to reach a load balanced state. The experimental results show that our algorithm not only obtains a compatible multi-resource load balancing performance but also improves the balanced time which results in at most a 10% throughput gain by assuming a large batch application running on all VMs.

The increasing demand for mobile data usage is overwhelming our wireless network. However, most of these devices are equipped with multiple network interfaces (multi-homed) which when properly exploited have the potential to increase bandwidth capacity and ensure reliable connectivity. But some technical challenges are restricting our multimode devices to using one single interface at a time. In this paper, we advocate for the use of multiple interfaces simultaneously, which can achieve reliable network connectivity, allow applications to distribute their traffic over multiple interfaces, and aggregate the capacity of different paths. We proposed an OpenFlow-based Multiple WLAN Interface (OpenMWF) prototype, designed by embedding OpenFlow network resource controller and a data forwarding open virtual switch (OVS) in the network stack of the device operating system. A proof of concept implementation and evaluation was carried out using Web-based Real-Time Communication (WebRTC) interactive video conferencing and multi-source downloading utility (Aria2c) applications use cases. The result showed the approach yielded benefits for applications performance, over single interface usage.

This study is motivated by a plan to install a software-defined wireless local area network (SDWLAN) on campus, which possesses a desired property that both data flow and device behaviors can be software-definable. Because the installation involves hundreds of access points, we must conduct simulations beforehand to verify the design and scalability of the target system. However, existing SDN simulator like Mininet does not support modeling of wireless channel and mobility. On the other hand, common network simulator like ns-3 only has limited support for software-defined controllers and does not fully implement handover process. We thus develop OpenNet, which connects Mininet to ns3 to enjoy both Mininet's advantage of controller compatibility and ns-3's ability in the wireless/mobility modeling. OpenNet also complements ns-3 by adding probe mechanism, which is missing in the current ns-3 implementation. Our simulation result demonstrates the effectiveness of OpenNet.

In recent years, with the economic development and urbanization, traffic congestion has become a serious problem in urban environments. Traffic signal control plays a key role in Intelligent Transportation System (ITS). Particularly, bus system can carry a higher capacity of passengers, which help to relief traffic jam in cities. However, different from ordinary vehicles, bus system has several unique features, including higher capacity of passengers, fixed routes and specific requirements on arrival time and headway. In this paper, we propose an adaptive traffic signal control approach with bus Priority that determines the phase sequence and time in non-fixed order based on synergic information to improve the performance of bus system with a very small cost to ordinary vehicles. Simulation results show that our approach can significantly reduce the waiting time of buses, keep bus schedules on time, and regular bus headway.

Researchers have developed several social-based routing protocols for delay tolerant networks (DTNs) over the past few years. Two main routing metrics to support a social-based routing in DTNs are centrality and similarity metrics. These two metrics help packets decide how to travel through the network to achieve a low delay or low drop rate. This study presents a new routing scheme called Community-Relevance based OPportunistic routing (CROP). CROP uses a different message forwarding approach in DTNs by combining community structure with a new centrality metric called community relevance. One fundamental change in this approach is that community relevance values do not represent the importance of communities themselves. Instead, they are computed for each community-community relationship individually which means that the level of importance of one community varies depending on the packet's destination community. This study compares CROP with other routing algorithms such as BubbleRap and SimBet. Simulation results show that CROP achieves an average delivery ratio improvement of at least 30% and can distribute packets more fairly within the network.

We consider the channel assignment problem in wireless mesh networks. Due to the limited number of radio interfaces that each node is equipped with, channel assignment must ensure that the interface constraint is obeyed, i.e., the number of different channels assigned to the links incident on a node must be no greater than the number of interfaces the node is equipped with. However, interface constraint may be one of the causes that hinder the performance of some of the existing heuristics. In this paper, we use simulated annealing to solve the channel assignment problem in wireless mesh networks. We propose two neighbor generating approaches that handle the interface constraint in different ways. The first approach starts with an infeasible random solution, and by using the penalty function technique the solution finally converges to a feasible one. The second approach, on the contrary, allows only feasible solutions to be generated during the simulated annealing process. Simulations are conducted that compare our proposed simulated annealing algorithms together with a tabu-based algorithm under different network traffic scenarios. The results show that our algorithms exhibit lower network interference than the tabu-based algorithm.

With the extension of wireless technology, vehicular ad hoc networks (VANETs) provide general data transmission services and emergency warning services. To rescue more drivers from being involved in an emergency event on the road, fast emergency message propagation is an important issue in VANET studies. There are two types of multi-hop broadcasting forwarder selection schemes for emergency broadcasting, known as sender-oriented schemes and receiver-oriented schemes. The sender-oriented schemes periodically maintain neighbor information in order to choose the best forwarder before broadcasting the message, while the receiver-oriented schemes distributed elect the forwarders. In this paper, we propose a vehicle-density-based emergency broadcast (VDEB) scheme to solve the problem of high overhead in sender-oriented schemes, and long delay in receiver-oriented schemes. The simulation results show that our VDEB scheme can achieve better performance with low delay and little overhead.

To cope with rapidly increasing Internet usage nowadays, providing Internet services using multiple servers has become a necessity. To ensure sufficient service quality and server utilization at the same time, effective methods are needed to spread load among servers properly. Existing load balancing methods often assume servers are homogeneous and consider only one type of resource, such as CPU. Such methods suffer from the fact that different requests often demand multiple types of resources with different requirements; trying to balance the usage of only one resource type may induce an inadvertent performance bottleneck, leading to low resource utilization and service quality. To address this problem, we propose a load balancing method based on the concept of distributed market mechanism, where requests are priced with respect to the load of multiple resources on each server. By migrating jobs among servers to balance inter-server load and minimize intra-server job cost at the same time, our method shows significant improvement in terms of load imbalance degrees, server utilization, and response time when compared to other published methods, especially when server heterogeneity increases.

This paper studies the problem of multicast routing and channel assignment in multi-channel and multi-interface wireless mesh networks. The advantage of the wireless broadcast's nature is used to reduce interference and improve network throughput. The employed network model is first described. Next, a heuristic channel assignment algorithm that makes use of the wireless broadcast's advantage is presented. Simulation results reveal that the proposed heuristic algorithm can reduce interference and increase the network throughput in multi-channel multi-interface wireless mesh networks.

The iLamp system is a sensor-enhanced desk lamp with surface-tracking capability based on received light intensity. It consists of two components: lamp and bookmark. The bookmark is a ZigBee-enabled sensor node that can report its sensed light intensity to the lamp with a user-friendly interface and two-way communication capability. The lamp can use its LEDs to locate user's reading surface to which the bookmark is attached, move toward the surface, and further tune its luminous intensity to meet user's preference. We develop the geometrical model for surface tracking. iLamp demonstrates a new centimeter-level location-tracking system using light intensity alone without other extra media or devices.

In this paper, we designed and implemented a dependable SIP-based clustered architecture for VoIP and multimedia applications, and also proposed an efficient OpenAIS-based SIP load balancing strategy (OSLB) that can balance proxy serverspsila load and achieve fast failover by reducing the number of failed calls when one of the dispatchers or one of the SIP proxy servers crashes. Experimental results show that our OSLB is comparable to an existing work, SIP load balancer, in terms of load balance metric (1.05 vs. 1.04). However, our OSLB reduces the number of failed calls by 86% when a proxy server failed compared to the SIP load balancer. This work, which is part of an EPON project, has been realized in an industry standard ATCA-based platform to provide high availability carrier-grade services, and is currently under a field trial in an ISP.

Since multi-hop mobile ad hoc network (MANET) contains a set of wireless mobile nodes forming a temporary network, the topology is strongly influenced by the node mobility models. Numerous mobility models have been presented, including the Random Waypoint Mobility Model (RWMM), Manhattan Grid Mobility Model (MGMM), Freeway Mobility Model (FMM), and so on. In MGMM, the trajectories of mobile nodes are confined to a grid topology. MGMM is an important mobility model, and numerous objects following MGMM can be enumerated, such as the movement of cars in the city, the movement of people though department stores etc. The expected link life time (ELLT) is an important performance parameter in MANET. When a node wishes to transmit information to the other node directly, these two nodes must be within each other's transmission range for a period of time. This period is called the link life time (LLT). The ELLT is the expected value of LLT. The goal of this work largely focuses on identifying the ELLT of the MANET under MGMM by using mathematical analysis. Based on our observation, two nodes involved in constructing a connection under MGMM can be classified into three independent cases: namely parallel with opposite directions, parallel with same directions, and vertical cases. These three cases can be formulated independently. To verify these formulations numerous simulations are done by ns2, and the theoretical and simulation results are well matched.

This paper proposes an energy-efficient traffic scheduling approach for 802.16e broadband wireless networks. Instead of considering a single Mobile Subscriber Station (MSS) as most of the current researchers do, multiple MSSs are considered in our work. The constant bit rate traffic with QoS delay constraint is considered in this paper. The proposed approach considers both energy efficiency and bandwidth utilization. First, we derive a minimum wakeup time for each MSS to achieve the maximum power saving by waking up the minimum number of time slots. After then, we interleave the traffic of multiple MSSs by taking advantage of feasible slot allocation. In order to support the maximum number of MSSs, our scheduling problem can be transformed into a maximum bipartite matching problem. We use the Ford-Fulkerson maximum flow algorithm to obtain a feasible schedule for multiple MSSs. Simulation results show that our proposed approach has better bandwidth utilization and achieves maximum energy saving.

This paper proposes a simple and scalable approach to multisink routing scheme in wireless sensor networks. Wireless sensor network is a rapidly growing discipline, with new technologies emerging and new applications under development. In addition to providing light and temperature measurements, wireless sensor nodes have applications such as security surveillance, environmental monitoring, and wildlife watching. One potential problem in a sensor network is how to transmit packets efficiently from Single-Source to Multi-Sinks, i.e., to gather data from a single sensor node and to deliver it to multiple clients who are interested in the data. The difficulty of such a scenario is finding the minimum-cost multiple transmission paths. Many routing algorithms have been proposed to solve this problem. Most current algorithms address the reduction of power consumption, and potentially introduce a large delay. This paper proposes a novel multi- path routing algorithm, called Hop-Count based routing (HCR) algorithm, which considers energy cost and transmission delay simultaneously. A hop count vector (HCV) is introduced to support routing decision. Moreover, an additional pruning vector (PV) can further enhance energy efficiency.

This paper proposes three energy efficient scheduling approaches for 802.16e broadband wireless networks. Instead of considering a single Mobile Subscriber Station (MSS) as most of the current researchers do, multiple MSSs are considered in our work. The constant bit rate traffic with QoS delay constraint is considered in this paper. The proposed approaches address both energy efficiency and bandwidth utilization. We reuse the idle fragmentation of the allocated OFDM frames to balance power saving and bandwidth utilization. Simulation results show that our proposed approaches benefit with more sleep time and higher bandwidth utilization. Furthermore, we give a QoS scheduling mechanism to find the maximum sleeping time for single MSS, called Minimum Wakeup Time (MWT) scheduler. Even though we don't know whether exists a feasible scheduling to satisfy all MSSs with MWT, it will serve as an upper bound for the power-saving scheduling in IEEE 802.16e.

This paper proposes a highly-available open shortest path first (HA-OSPF) router which consists of two OSPF router modules-active and standby-to support a high-availability network. Each router module runs a Linux operating system, high-availability management middleware (HAM middleware), and OSPF daemon. The HAM middleware consists of an availability management framework (AMF) service, checkpoint service, interface monitor, OSPF fault manager, and fault handler; it provides a health check, state information exchange, and takeover mechanism. The experimental results are given to show the system availability of the HA-OSPF router on a PC-based prototype system. Furthermore, to build a carrier grade commercial product, we realize a HA-OSPF router on an industry standard compliant advanced telecom computing architecture (ATCA) hardware platform. From actual measurements, we show that our PC-based and ATCA-based HA-OSPF routers take only 166 and 131 ms to switch over to a standby router module when there is a software fault and 360 and 331 ms with a hardware failure respectively.

Wireless sensor network is a rapidly growing discipline with new technologies emerging, and new applications under development. The nodes in a wireless network generally communicate with each other along the same wireless channel. Unfortunately, sharing among wireless channels decreases network performance due to radio interference, and also raises energy consumption due to packet retransmission when interference occurs. Many topology control algorithms have been proposed to solve these problems. One widely used strategy is the backbone method. Backbone algorithms aim to reduce the backbone size. However, poor performance may be explored if only few backbone nodes are selected. Therefore, several heuristic algorithms such as SBC have been proposed. However, these algorithms cannot efficiently eliminate redundant nodes, and dramatically decrease performance, especially in relatively sparse networks. This study proposes a novel heuristic-based backbone algorithm called SmartBone to choose proper backbone nodes from a network. SmartBone includes two major mechanisms. Flow-bottleneck preprocessing is adopted to find critical nodes, which act as backbone nodes to improve connectivity. Dynamic density cutback is adopted to reduce the number of redundant nodes depending on local area node density of network. SmartBone simultaneously considers the balance of network performance and energy savings. Significantly, the proposed algorithm has a 50% smaller backbone size than SBC, and improves the energy saving ratio from 25% using SBC to 40% using SmartBone. Moreover, SmartBone improves the packet delivery ratio from 40% to 90% when the density of sensor networks becomes relatively sparser.

Wireless mesh networks (WMNs) are emerging as a favorable technology for last-mile Internet access. Nodes in WMNs can be equipped with multiple interfaces which work in different channels to increase the available bandwidth. However, efficient channel assignment schemes are still needed due to the interference effect and the limited number of orthogonal channels. In this paper, we consider the channel assignment and routing for dynamic traffic in WMNs. We adopt the static channel assignment strategy to the network interfaces. The problem is simplified into two sequential stages. The first is to assign channels to interfaces while the second is to determine the route for each coming traffic demand. We propose a Mixed Integer Linear Programming (MILP) formulation to the problem and develop a simulated annealing based channel assignment algorithm for the channel assignment. The shortest path routing is adopted for the dynamic traffic. Simulation results show the network throughput and blocking probability under different network scenarios.

As the technology advances to increase the number of wavelengths in fiber links, multigranularity optical cross-connects (MG-OXCs) have emerged as a solution to reduce the manufacturing cost of the traditional optical cross-connects (OXCs). In this paper, we aim to provide an efficient fault-recovery protection scheme for the lightpaths in the MG-OXC networks. A segment-based protection scheme, called tunnel based segment protection (TSP) is proposed to recover the communications interrupted by a fiber cut. TSP first allocates all the tunnels off-line according to the historical traffic matrix and then starts to serve the incoming requests. When allocating a tunnel, a backup tunnel is always allocated as well. Consequently, a lightpath is naturally divided into segments according to the switching types along the path. Therefore, after a working path is found for a connection request, only a shared backup path for those segments in the corresponding wavelength-switching layers need to be found. In addition, TSP utilizes wavelength-switching ports efficiently since working and backup tunnels can share the same wavelength-switching ports at two ends of the tunnel. Simulation results show that the network performance is improved comparing to adapt a straightforward path protection scheme for MG-OXC networks.

In order to support Internet security, virtual private networks, QoS, etc., Internet routers need to classify incoming packets quickly into flows. A packet classifier uses information contained in the packet header and a predefined rule table in the routers to classify the packets. This paper presents a novel packet classification algorithm, called the bit compression algorithm. Like the previously best known algorithm, bitmap intersection, bit compression is based on the multiple dimensional range lookup approach. Since the bit vectors of the bitmap intersection contain lots of '0' bits, the bit vectors could be compressed. We compress the bit vectors by preserving useful information but removing the redundant '0' bits of the bit vectors. Additionally, the wildcard rules also enable more extensive improvement. Comparing with the bitmap intersection algorithm, the bit compression algorithm reduces the storage complexity in the average-case from thetas (dN2) to thetas (dN-logN), where d denotes the number of dimensions and N represents the number of rules. By exploring the memory hierarchy, we show that bit compression algorithm requires much less memory access than bitmap intersection algorithm on Intel IXP1200 network processor. Since memory access dominates the lookup time, even though extra decompression time is required for bit compression scheme, the bit compression scheme in the average still outperforms bitmap intersection scheme on the classification performance

We consider the problem of routing and assignment of wavelength (RAW) in optical networks. Given a set of requests for all-optical connections (or lightpaths), the problem is to (a) find routes from the source nodes to their respective destination nodes, and (b) assign wavelengths to these routes. Since the number of wavelengths is limited, lightpaths cannot be established between every pair of access nodes. In this paper we first consider the dynamic RAW problem where lightpath requests arrive randomly with exponentially distributed call holding times. Then, the static RAW problem is considered which assumes that all the lightpaths that are to be set-up in the network are known initially. Several heuristic algorithms have already been proposed for establishing a maximum number of lightpaths out of a given set of requests. However most of these algorithms are based an the traditional model of circuit-switched networks where routing and wavelength assignment steps are decoupled. In this paper a new graph-theoretic formulation of the RAW problem, dubbed as layered-graph, has been proposed which provides an efficient tool for solving dynamic as well as static RAW problems. The layered-graph model also provides a framework for obtaining exact optimal solution for the number of requested lightpaths as well as far the throughput that a given network can support. A dynamic and two static RAW schemes are proposed which are based on the layered-graph model. Layered-graph-based RAW schemes are shown to perform better than the existing ones.