This paper presents an autonomous traffic engineering framework, named ATE, a highly efficient data dissemination mechanism for multipath data forwarding in Wireless Sensor Networks (WSNs). The proposed ATE has several salient features. First, ATE utilizes three coordinating schemes: an incipient congestion inference scheme, an accurate link quality estimation scheme and a dynamic traffic diversion scheme. It significantly minimizes packet drops due to congestion by dynamically and adaptively controlling the data traffic over congested nodes and/or poorer quality links, and by opportunistically exploiting under-utilized nodes for traffic diversion, while minimizing the estimation and measurement overhead. Second, ATE can provide with high application fidelity of the network even for increasing values of bit error rates and node failures. The proposed link quality estimation and congestion inference schemes are light weight and distributed, improving the energy efficiency of the network. Autonomous Traffic Engineering has been evaluated extensively via NS-2 simulations, and the results have shown that ATE provides a better performance with minimum overhead than those of existing approaches.

Broadband wireless access networks are promising technology for providing better end user services. For such networks, designing a scheduling algorithm that fairly allocates the available bandwidth to the end users and maximizes the overall network throughput is a challenging task. In this paper, we develop a centralized fair scheduling algorithm for IEEE 802.16 mesh networks that exploits the spatio-temporal bandwidth reuse to further enhance the network throughput. The proposed mechanism reduces the length of a transmission round by increasing the number of non-contending links that can be scheduled simultaneously. We also propose a greedy algorithm that runs in polynomial time. Performance of the proposed algorithms is evaluated by extensive simulations. Results show that our algorithms achieve higher throughput than that of the existing ones and reduce the computational complexity.

Network congestion and random errors of wireless link are two well-known noteworthy parameters which degrade the TCP performance over heterogeneous networks. We put forward a novel end-to-end TCP congestion control mechanism, namely TCP BaLDE (Bandwidth and Loss Differentiation Estimate), in which the TCP congestion control categorizes the reason of the packet loss by estimating loss differentiation in order to control the packet transmission rate appropriately. While controlling transmission rate depends on the available bandwidth estimation which is apprehended by the bandwidth estimation algorithm when the sender receives a new ACK with incipient congestion signal, duplicates ACKs or is triggered by retransmission timeout event. Especially, this helps the sender to avoid router queue overflow by opportunely entering the congestion avoidance phase. In simulation, we experimented under numerous different network conditions. The results show that TCP BaLDE can achieve robustness in aspect of stability, accuracy and rapidity of the estimate in comparison with TCP Westwood, and tolerate ACK compression. It can achieve better performance than TCP Reno and TCP Westwood. Moreover, it is fair on bottleneck sharing to multiple TCP flows of the same TCP version, and friendly to existing TCP version.

In this paper, we propose a scalable service networking architecture as a TINA-like environment for providing flexibly various mobility services. The proposed architecture provides an environment that enables the advent of service providers and rapidly introduces multimedia applications, considering networks scalability. For supporting customized mobility services, this architecture adopts a new service component, which we call Omnipresent Personal Environment Manager (OpeMgr). In order to support mobile users who move between heterogeneous networks, for instance, between the TINA-like environment and the Internet environment, we propose a structure of a gateway. In addition, the proposed architecture uses the fixed and mobile agent approaches for supporting the user's mobility, and we evaluated their performances with comparing those approaches.

Cubic TCP, one of transport protocols designed for high bandwidth-delay product (BDP) networks, has successfully been deployed in the Internet. Multi-homed computers with multiple interfaces to access the Internet via high speed links will become more popular. In this work, we introduce an extended version of Cubic TCP for multiple paths, called MPCubic. The extension process is approached from an analysis model of Cubic by using coordinated congestion control between paths. MPCubic can spread its traffic across paths in load-balancing manner, while preserving fair sharing with regular TCP, Cubic, and MPTCP at common bottlenecks. Moreover, to improve resilience to link failure, we propose a multipath fast recovery algorithm. The algorithm can significantly reduce the recovery time of data rate after restoration of failed links. These techniques can be useful for resilient high-bandwidth applications (for example, tele-health conference) in disaster-affected areas. Our simulation results show that MPCubic can achieve stability, throughput improvement, fairness, load-balancing, and quick data rate recovery from link failure under a variety of network conditions.

Distributed Denial-of-Service attack (DDoS) is one of the most outstanding menaces on the Internet. A DDoS attack generally attempts to overwhelm the victim in order to deny their services to legitimate users. A number of approaches have been proposed for defending against DDoS attacks accurately in real time. However, existing schemes have limits in terms of detection accuracy and delay if the IDRS (Intrusion Detection and Response System) deployed only at a specific location detects and responds against attacks. As in this case, it is not able to catch the characteristic of the attack which is distributed in large-scale. Moreover, the existing detection schemes have vulnerabilities to intellectual DDoS attacks which are able to avoid its detection threshold or delay its detection time. This paper suggests the effective DDoS defense system which uses the collaborative scheme among distributed IDRSs located in the vicinity of the attack source or victim network. In proposed scheme, both victim and source-end IDRS work synergistically to identify the attack and avoid false alarm rate up to great extent. Additionally, we propose the duplicate detection window scheme to detect various attacks dynamics which increase the detection threshold gradually in early stage. The proposed scheme can effectively detect and respond against these diverse DDoS attack dynamics.

This letter proposes a new fast network configuration scheme that realizes an IP interface that allows users to view Internet Protocol TV (IPTV) in IPv6 networks more quickly than is possible with the current configuration procedure. The new scheme, a hybrid combination of IPv6, address information, and non-IP information, especially the Domain Name Service, is newly designed based on a technical analysis. The evaluation results show that the proposed scheme is acceptable for real-time television watching in IPv6 networks, even when in motion.

Nowadays portable devices with multiple wireless interfaces and using multimedia services are becoming more popular on the Internet. This paper describes a family of multipath binomial congestion control algorithms for audio/video streaming, where a low variant of transmission rate is important. We extend the fluid model of binomial algorithms for single-path transmission to support the concurrent transmission of packets across multiple paths. We focus on the extension of two particular algorithms, SQRT and IIAD, for multiple paths, called MPSQRT and MPIIAD, respectively. Additionally, we apply the design technique (using the multipath fluid model) for multipath TCP (MPTCP) into the extension of SQRT and IIAD, called fbMPSQRT and fbMPIIAD, respectively. Both two approaches ensure that multipath binomial congestion control algorithms achieve load-balancing, throughput improvement, and fairness to single-path binomial algorithms at shared bottlenecks. Through the simulations and comparison with the uncoordinated protocols MPSQRT/MPIIAD, fbMPSQRT/fbMPIIAD and MPTCP, we find that our extended multipath transport protocols can preserve lower latency and transmission rate variance than MPTCP, fairly share with single-path SQRT/IIAD, MPTCP and TCP, and also can achieve throughput improvements and load-balancing equivalent to those of MPTCP under various scenarios and network conditions.

Sensor networks that carry heterogeneous traffics and are responsible for reporting very time-critical important events necessitate an efficient and robust data dissemination framework. Designing such a framework, that can achieve both the reliability and delay guarantee while preserving the energy efficiency, namely multi-constrained QoS (MCQoS), is a challenging problem. Although there have been many research works on QoS routing for sensor networks, to the best of our knowledge, no one addresses the above three service parameters all together. In this paper, we propose a new aggregate routing model and a distributed aggregate routing algorithm (DARA) that implements the model for achieving MCQoS. DARA is designed for multi-sink, multipath and location aware network architecture. We develop probabilistic models for multipath reliability constraint, sojourn time of a packet at an intermediary node and node energy consumption. Delay-differentiated multi-speed packet forwarding and in-node packet scheduling mechanisms are also incorporated with DARA. The results of the simulations demonstrate that DARA effectively improves the reliability, delay guarantee and energy efficiency.

The aggregate throughput of wireless mesh networks (WMNs) can be significantly improved by equipping the mesh routers with multiple radios tuned to orthogonal channels. Not only the links using orthogonal channels can be activated at a time, but some links in the same channel also can be activated concurrently if the Signal-to-Interference-and-Noise Ratio (SINR) at their receivers is not lower than the threshold, which is the spatial-reuse characteristic. STDMA is considered as one of the medium access schemes that can exploit spatial reuse to improve network throughput. Past studies have shown that optimizing the performance of STDMA is NP-Hard. Therefore, we propose a STDMA-based scheduling algorithm that operates in a greedy fashion for WMNs. We show that the proposed algorithm enhances not only the throughput but also the fairness by capturing the essence of spatial-reuse approach of STDMA and giving medium access opportunities to each network element based on its priority. We furthermore validate our algorithm through theoretical analysis and extensive simulations and the results show that our algorithm can outperform state-of-the-art alternatives.

The intent of this letter is to propose an efficient timestamp based password authentication scheme using smart cards. We show various types of forgery attacks against Shen et al.'s timestamp-based password authentication scheme and improve their scheme to ensure robust security for the remote authentication process, keeping all the advantages of their scheme. Our scheme successfully defends the attacks that could be launched against other related previous schemes.

We study joint rate control and resource allocation with a packet collision constraint that maximizes the total utility of secondary users in cognitive radio networks. We formulate and decouple the original optimization problem into separable subproblems and then develop an algorithm that converges to optimal rate control and resource allocation. The proposed algorithm can operate on different time-scales to reduce the amortized time complexity.

In this paper, a hybrid overlay/underlay cognitive radio system is modeled as an M/M/1 queue where the rate of arrival and the service capacity are subject to Poisson alternations. Each packet as a customer arriving at the queue makes a decision to join the queue or not. Upon arrival, the individual decision of each packet is optimized based on his observation about the queue length and the state of system. It is shown that the individually optimal strategy for joining the queue is characterized by a threshold of queue length. Thus, the individual optimal threshold of queue length is analyzed in detail in this work.

For successful data collection in wireless sensor networks, it is important to ensure that the required delivery ratio is maintained while keeping a fair rate for every sensor. Furthermore, emerging high-rate applications might require complete reliability and the transfer of large volume of data, where persistent congestion might occur. These requirements demand a complete but efficient solution for data transport in sensor networks which reliably transports data from many sources to one or more sinks, avoids congestion and maintains fairness. In this paper, we propose congestion-aware and rate-controlled reliable transport (CRRT), an efficient and low-overhead data transport mechanism for sensor networks. CRRT uses efficient MAC retransmission to increase one-hop reliability and end-to-end retransmission for loss recovery. It also controls the total rate of the sources centrally, avoids the congestion in the bottleneck based on congestion notifications from intermediate nodes and centrally assigns the rate to the sources based on rate assignment policy of the applications. Performance of CRRT is evaluated in NS-2 and simulation results demonstrate the effectiveness of CRRT.

The increase in network access devices and demand for high quality of service (QoS) by the users have led to insufficient capacity for the network operators. Moreover, the existing control equipment and mechanisms are not flexible and agile enough for the dynamically changing environment of heterogeneous cellular networks (HetNets). This non-agile control plane is hard to scale with ever increasing traffic demand and has become the performance bottleneck. Furthermore, the new HetNet architecture requires tight coordination and cooperation for the densely deployed small cell base stations, particularly for interference mitigation and dynamic frequency reuse and sharing. These issues further complicate the existing control plane and can cause serious inefficiencies in terms of users' quality of experience and network performance. This article presents an SDN control framework for energy efficient downlink/uplink scheduling in HetNets. The framework decouples the control plane from data plane by means of a logically centralized controller with distributed agents implemented in separate entities of the network (users and base stations). The scheduling problem consists of three sub-problems: (i) user association, (ii) power control, (iii) resource allocation and (iv) interference mitigation. Moreover, these sub-problems are coupled and must be solved simultaneously. We formulate the DL/UL scheduling in HetNet as an optimization problem and use the Markov approximation framework to propose a distributed economical algorithm. Then, we divide the algorithm into three sub-routines for (i) user association, (ii) power control, (iii) resource allocation and (iv) interference mitigation. These sub-routines are then implemented on different agents of the SDN framework. We run extensive simulation to validate our proposal and finally, present the performance analysis.

Cognitive radio is one of the most promising wireless technologies and has been recognized as a new way to improve the spectral efficiency of wireless networks. In a cognitive radio network, secondary users exchange control information for network coordination such as transmitter-receiver handshakes, for sharing spectrum sensing results, for neighbor discovery, to maintain connectivity, and so on. Spectrum utilization and resource optimizations thus rely on information exchange among secondary users. Normally, secondary users exchange the control information via a predefined channel, called a common control channel (CCC). Most of the medium access control (MAC) protocols for cognitive radio networks were designed by assuming the existence of a CCC, and further assuming that it was available for every secondary user. However, the main drawback of using a static CCC is it is susceptible to primary user activities since the channel can be occupied by primary users at any time. In this paper, we propose a MAC protocol for cognitive radio networks with dynamic control channel assignment, called DYN-MAC. In DYN-MAC, a control channel is dynamically assigned based on spectrum availability. Thus, it can tolerate primary user activities. DYN-MAC also supports collision free network-wide broadcasting and addresses other major problems such as primary/secondary user hidden terminal problems.

Sensors have very scarce resources in terms of memory, energy and computational capacities. Wireless sensor network is composed of a large number of such sensor nodes densely deployed in inhospitable physical environments. Energy efficient information dissemination throughout such a network is still a challenge. Though dissemination of information with minimum energy consumption is a key concern in wireless sensor networks, it often introduces additional delay. In this work, we first propose an energy and delay efficient multi-hop routing scheme called C2E2S (Cluster and Chain based Energy*Delay Efficient Routing Scheme) for wireless sensor networks. This scheme is a combination of cluster-based and chain-based approaches and the way to form clusters and chains in this work is center-based approach. To reduce a large number of communication overheads due to this approach, we propose a modified-center-based approach called passive-BS-based approach. Next, we propose (1) an energy and delay aware routing algorithm for sensors within each k-hop cluster, and (2) an Energy-efficient chain construction algorithm for cluster heads. To evaluate the appropriateness of our approach, we analyze the evaluated performance against existing protocols in terms of communication overhead, the number of communication rounds (network lifetime), total amount of energy dissipated in the system over time, network delay and Energy*Delay metric using SENSE simulator. The simulation results show that C2E2S consumes less energy, balances the energy and delay metrics, and extends the network lifetime as compared to other approaches.

Multimedia service users can require multi-services according to their own environment for accessing to public networks. For copying with customer-oriented service requirements, network providers have to prepare multi-layer service networks. This paper deals with frame relay, ATM and IP networking services on multi-layer networks. In order to provide multiple data services, network provider needs to define and make use of client-server and interworking relationships between these networks. In this paper, we propose a service management architecture in order to efficiently manage multiple services and network resources from service point of view. The proposed service management architecture includes functionalities such as subscription management, customer-network management, communication session management, and business layer support management. Especially, it describes an information model for managing multi-layer networks by way of the interworking or client-server relationship. The proposed functionalities are modeled in accordance with the object-oriented modeling concept and implemented on a CORBA platform. The applications on the proposed architecture include VPN services and various statistical services for customers and the carrier. The realized system is to be used for Koera Telecom's high speed networks mainly for supporting Internet services.

Security for wireless sensor networks (WSNs) has become an increasingly serious concern due to the requirement level of applications and hostile deployment areas. To enable secure services, cryptographic keys must be agreed upon by communicating nodes. Unfortunately, due to resource constraints, the key agreement problem in wireless sensor networks has become quite complicated. To tackle this problem, many public-key unrelated proposals which are considered more reasonable in cost than public key based approaches have been proposed so far including random based key pre-distribution schemes. One prominent branch of these proposals is threshold random key pre-distribution schemes. However these schemes still introduce either communication overhead or both communication and computational overheads to resource constrained sensor nodes. Considering this issue, we propose an efficient ID-based threshold random key pre-distribution scheme that not only retains all the highly desirable properties of the schemes including high probability of establishing pairwise keys, tolerance of node compromise but also significantly reduces communication and computational costs of each node. The proposed scheme is validated by a thorough analysis in terms of network resiliency and related overheads. In addition, we also propose a supplementary method to significantly improve the security of pairwise keys established indirectly.

The overall performance of multi-hop cognitive radio networks (MHCRNs) can be improved significantly by employing the diversity of orthogonal licensed channels in underlay fashion. However, the mutual interference between secondary links and primary links and the congestion due to the contention among traffic flows traversing the shared link become obstacles to this realizing technique. How to control congestion efficiently in coordination with power and spectrum allocation optimally in order to obtain a high end-to-end throughput is motivating cross-layer designs for MHCRNs. In this paper, by taking into account the problem of joint rate adaption, power control, and spectrum allocation (JRPS), we propose a new cross-layer optimization framework for MHCRNs using orthogonal frequency division multiple access (OFDMA). Specifically, the JRPS formulation is shown to be a mix-integer non-linear programming (MINLP) problem, which is NP-Hard in general. To solve the problem, we first develop a partially distributed algorithm, which is shown to converge to the global optimum within a reasonable time interval. We next propose a suboptimal solution which addresses the shortcomings of the first. Using numerical results, we finally demonstrate the efficiency of the proposed algorithms.