The demand for Low-earth-orbit (LEO) satellite networking and routing is continuously growing. Container-based satellite network emulation becomes an important networking evaluation choice for LEO satellite network. While many container-based satellite network emulators optimize virtual network efficiency, they often overlook route installation latency—the duration of installing computed routes into kernel routing table. This latency represents a significant bottleneck for emulating large-scale LEO constellations, which are characterized by dynamic topologies and frequent, massive routing re-convergences. High routing installation latency not only reduces emulation efficiency but also compromises evaluation reliability and renders subsequent data transmission experiments infeasible. In this paper, we present a Lock-Free and Filtered Route Installation (LFRI) mechanism. LFRI filters out non-effective route installations, thereby shortening the installation procedure without changing the routing results. LFRI employs a lock-free installation mechanism that enables parallelized and efficient route installation. Experimental results demonstrate that, compared to the legacy Netlink installation, LFRI reduces the route installation latency by up to 99.9% in emulations of typical LEO satellite constellations, bringing it down to under ten milliseconds, within a performance level comparable to routing installation on physical machines. Meanwhile, in the case study evaluating path availability ratio and restoration time, LFRI yields more consistent and credible experimental data.

With the steady development of geostationary orbit (GEO) satellites in China and the accelerated construction of low-orbit (LEO) satellite internet, the integration application of high and low orbit heterogeneous constellations has become an important direction for future development. Current research mainly focuses on resource allocation within a single constellation, such as GEO constellations or LEO constellations, while there is insufficient attention to the collaborative allocation of heterogeneous resources in mixed high and low orbit and cross-constellation scenarios. Therefore, this paper takes the China-Sat, Asia-Pacific and LEO satellite internet systems as research objects, deeply analyzes the service transmission modes and resource characteristics of different satellite systems such as transparent forwarding, high throughput and LEO constellations. At the same time, from the current engineering construction status, a heterogeneous resource allocation strategy for cross-high and low orbit mixed satellite networks is proposed. This strategy takes dynamic communication service demands as input and collaboratively allocates beam bandwidth, frequency, time slot, power and inter-satellite links and other heterogeneous resources. The research results can provide support for the simulation modeling and business planning of high and low orbit mixed satellite networks.

As the frequency of cyber attacks (e.g., DDoS) continues to rise, it becomes increasingly crucial to trace malicious packets and identify which autonomous systems (ASes) they originate from and traverse through. Path-aware networking (PAN) architectures, forwarding packets based on in-packet path identifiers (PIDs), enable end-hosts to gain insights into the AS-level topology and facilitate AS-level path traceback. However, the study on AS-level topology inference and path traceback under PAN has been overlooked, primarily due to the diversity of path identification. Some PAN architectures (e.g., SCION) use deterministic PIDs to identify inter-domain paths, while others (e.g., CoLoR) adopt prefix-deterministic PIDs. In the latter, PID-Prefix is used to identify inter-domain paths, and PID-Suffix is reserved for additional security functions, making the inference problem complicated. This paper focuses on PAN with prefix-deterministic PIDs and investigates how to use in-packet PIDs to infer the AS-level topology. Our goal is to construct a tree-like AS-level topology with the corresponding PID-Prefixes based on in-packet PIDs. We first introduce two macro metrics (i.e., completion rate and precision rate) and two micro metrics (i.e., traceback division and traceback aggregation) to evaluate the inference accuracy. Furthermore, we propose an Alternating Expanding and Checking (AEC) algorithm for AS-level topology inference. AEC algorithm constructs the topology by iteratively expanding and checking the current topology. The expanding phase performs one-hop PID-Prefix inference and generates new child ASes, while the checking phase verifies the consistency of PID sequences with the current topology from the perspective of each new child AS. Experiments based on empirical Internet topology of 201 ASes show that the accuracy of AEC reaches 99.6% when the observer receives only 30 packets from each AS.

IoT devices have become deeply integrated into our daily lives, making comprehensive security research on critical infrastructure devices increasingly important. Static analysis techniques, particularly those leveraging taint propagation, have demonstrated promise in identifying security vulnerabilities within these devices, effectively detecting critical vulnerabilities. However, current solutions often struggle with limitations in both detection efficiency and accuracy. To address these challenges, this paper introduces Liva, a novel static taint analysis tool designed for detecting web vulnerabilities in IoT devices. Liva employs a large language model (LLM) multi-agent approach for static binary taint analysis, primarily leveraging fine-tuned open-source models and commercial LLMs to improve source/sink identification and taint data analysis—areas where traditional methods often fall short—thereby enhancing overall analysis efficiency. LIVA's core analysis engine leverages a Qwen3-32B open-source model that has been fine-tuned using a dataset of 3,000 real-world device samples. This fine-tuned model achieves a 3 percentage point improvement in accuracy for identifying taint data propagation relationships compared to commercial LLMs, while also increasing average analysis efficiency by 5.5%. A comprehensive evaluation of Liva, conducted on a dataset of 64 devices from 11 vendors, revealed that it detected 309 and 349 more known vulnerabilities than the state-of-the-art solutions SaTC and Karonte, respectively, while simultaneously reducing false positive rates by 59.4% and 67.6%. Liva achieves a recall of 98.1% and a precision of 74.6%, with a 6.7× reduction in analysis time compared to the best-performing baseline. Furthermore, in the realm of zero-day vulnerability detection, Liva discovered 64 previously unknown vulnerabilities, 39 of which have since been assigned official CVE/CNVD identifiers.

Acquiring the status information of candidate servers is important for decision making in edge computing, which is however extremely challenging and time-consuming in high-dense device-assisted task offloading scenarios. In this paper, we propose a Distributed Status-aware response (DiSar) method to balance the status acquisition and task execution latency by utilizing incomplete but necessary status information. Specifically, each candidate server device set a backoff timer based on their computing and transmission status independently, which enables low-latency servers to rapidly respond while avoiding wireless transmission collisions. A salient-driven status mapping algorithm is proposed for the backoff timer setting, and the performances of DiSar are analyzed theoretically. Accordingly the influencing parameters are further optimized to rapidly fit the dynamic offloading environment, whereby the performances of DiSar are guaranteed. Simulation results demonstrate that DiSar can find the optimal server device with 95% probability while reducing the information acquisition latency by 96.33%, compared with centralized complete information acquisition. In addition, the overall task offloading latency can be reduced by 11.63% to 52.67%, using DiSar compared with the state-of-theart methods.

Due to the intermittent nature of wireless transmission, link state awareness is important to enhance the success probability and efficiency of unmanned aerial vehicles (UAV) networking, which is however resource consuming especially in the high mobility scenario. In this paper, we utilize the broadcast feature of wireless channels to infer the real-time link state along with packet forwarding, and propose a reception determined routing (RDR) mechanism. Specifically, for each hop, the transmission node broadcasts the packet, and multiple reception nodes together decide the optimal one to forward the packet based on packet reception, network topology, and historical paths. The key challenge lies in making appropriate decisions based on fused information distributively. A path repair mechanism is also proposed to further enhance routing reliability by dealing with node mobility and link down. Packetlevel simulation results show that RDR achieves a higher packet delivery ratio (up to 62.3 %) and supports larger network scales (up to 79.5 % improvements) compared to state-of-the-art mechanisms.

Cloud service centers (CSCs) can purchase edge computation resources to improve service quality in mobile cloud-edge computing networks. However, edge servers (ESs) are owned by different entities, and dishonest entities may launch computational forgery attacks, i.e., the ES falsely reports its idle computation resources to win more tasks for increased revenue. Most existing approaches ignore the threat of dishonest ESs. To address the challenges, we design aTrust-basedComputationOffloading (TCO) framework. First, we construct the problem for minimizing thedifference between the CSC'scost and theexpectedrevenue (DCER), which is a mixed-integer nonlinear programming problem. Second, we develop a trust-based computation offloading method that quickly finds a good solution by decomposing the problem. Finally, a two-tier trust evaluation method was proposed to obtain accurate trust values. Experimental results indicate that TCO's comprehensive performance surpasses the benchmarks and significantly enhances computation offloading reliability with a lower performance loss. Notably, tasks are preferentially offloaded to honest ESs to ensure their revenue and promote ESs’ honesty under the TCO framework. Additionally, compared with no trust mechanisms, TCO reduces the service timeout count in an interval by 34.37% - 73.80% with a performance loss of only 1.42% - 4.10%.

Low-earth-orbit (LEO) mega-constellations with inter-satellite links (ISLs) are becoming the Internet backbone in space. Satellites within LEO often need the capability to enforce data forwarding paths. For example, they may need to bypass the satellites over the untrusted areas for the data of mission-critical applications or minimize latency for the data of time-sensitive applications. However, typical source/segment routing techniques (e.g., SRv6) suffer from scalability issue, since they record source-route-style forwarding information via the list-based structure. This results in great payload and forwarding overhead. To overcome this drawback, we propose a source/segment routing architecture for LEO mega-constellations, which is named as Link-identified Routing (LiR). LiR leverages in-packet bloom filter (BF) to record source-route-style forwarding information. BF could efficiently record multiple elements via a probabilistic data structure, but overlooks the order of the encoded elements. To address this, LiR identifies each unidirectional ISL, and represents the path by encoding ISL identifiers into BF. We investigate how to optimize BF configuration and ISL encoding policy to address false positives caused by BF. We implement LiR in Linux kernel and develop a container-based emulator for performance evaluation. Results show that LiR significantly outperforms SRv6 in terms of packet forwarding and data delivery efficiency.

Many Internet platforms are information-oriented and crowd-based. They collect fresh information of various points of interest (PoIs) relying on users who happen to be nearby the PoIs. The platform will offer rewards to incentivize users and compensate their costs incurred from information acquisition. In practice, a user’s cost is his/her private information, thus both the user cost and its distribution are hidden to the platform, making it challenging to determine the optimal rewarding decision. In this paper, we investigate how the platform dynamically rewards the users, aiming to jointly reduce the age of information (AoI) and the operational expenditure (OpEx). Due to the hidden cost distribution, this is an online non-convex learning problem with bandit feedback. To overcome the challenge, we first design an age-based reward scheme, which decouples the OpEx from the unknown cost distribution and enables the platform to accurately control its OpEx. We then take advantage of the age-based reward scheme and propose an exponentially discretizing and learning (EDAL) policy for platform operation. We prove that the EDAL policy performs asymptotically as well as the optimal decision (derived from the cost distribution). Simulation results show that the age-based reward scheme protects the platform’s OpEx from the influence of the user crowd characteristics, and also verify the asymptotic optimality of the EDAL policy.

Mobile crowdsourcing (MCS) has attracted widespread attention by recruiting users with mobile devices to collect crowdsourcing data. Existing research on MCS assumes that the platform has sufficient users. However, platforms in their early stages of development face the cold start problem, which can lead to their inability to grow or even result in bankruptcy. While some studies try to solve it by recruiting users through social networks to participate in crowdsourcing tasks, they only focus on how to recruit more users without addressing the issue of user retention. This can lead to an increasing proportion of users losing interest in the platform and dropping out and thus it fails to solve the cold start problem truly. In light of this, we present a task recommendation-based method to recruit new users via the social network and keep registered users active on the platform. Specifically, we first use an extended independent cascade model to describe the recruitment of users through social networks. Secondly, we use a task acceptance model to describe user decisions. Finally, we utilize a fuzzy control system that incorporates spatiotemporal crowdsourcing information to predict user behaviour and recommend tasks to users most likely to complete them. Extensive experiments on large-scale real datasets were conducted to evaluate the proposed solution. The results indicate that compared to existing methods such as SocialRecruiter, our solution reduces the 30-day average user churn rate by 23.90% while significantly boosting user retention and task completion rates by up to 23.73% and 48.7%, respectively.

Low-Earth-Orbit (LEO) satellite constellation is promising to extend broadband Internet services to where the terrestrial networks cannot reach, forming a satellite-terrestrial integrated network (STIN). The tradeoff between communication latency and topology stability is the core of constellation design and STIN operation. In general, low-altitude orbits reduce the propagation delay of ground-satellite links (GSLs), but result in frequent handover for GSLs. Frequent GSL handover weakens the topology stability, which is often measured by satellite pass duration and communication session duration. In this paper, we investigate the latency-stability tradeoff in STIN, and propose a stochastic model to analyze and evaluate GSL latency and pass/session duration. We analytically derive the distributions and the expectations of these metrics in closed forms, and verify the theoretic results based on empirical distributions (obtained by trajectory simulation). Compared to previous studies, our results exhibit more concise expressions and arguments. We find that the above closed-form expressions take two key arguments, i.e., the orbit period and the maximal central angle. The expected pass/session duration is directly proportional to the product of the two arguments, and the coefficients can be obtained explicitly (e.g., 0.25 for pass duration). We also demonstrate how to utilize the analytic results to draw deep insights on constellation design, aiming to reduce the GSL latency and keep the topology stable. We believe that our results in this paper could empower the operators and researchers to obtain a rapid understanding on the latency-stability tradeoff of STIN without resorting to time-consuming simulations.

In decentralized edge computing environments, user devices need to perceive the status of neighboring devices, including computational availability and communication delays, to optimize task offloading decisions. However, probing the real-time status of all devices introduces significant overhead, and probing only a few devices can lead to suboptimal decision-making, considering the massive connectivity and non-stationarity of edge networks. Aiming to balance the status probing cost and task offloading performance, we study the joint transmission and computation status probing problem, where the status and offloading delay on edge devices are characterized by general, bounded, and non-stationary distributions. The problem is proved to be NP-hard, even with known offloading delay distributions. To handle this case, we design an efficient offline method that guarantees a$(1-1/e)$approximation ratio via leveraging the submodularity of the expected offloading delay function. Furthermore, for scenarios with unknown and non-stationary offloading delay distributions, we reformulate the problem using the piecewise-stationary combinatorial multi-armed bandit framework and develop a change-point detection-based online status probing (CD-OSP) algorithm. CD-OSP can timely detect environmental changes and update probing strategies via using the proposed offline method and estimating offloading delay distributions. We prove that CD-OSP achieves a regret of$\mathcal {O}(NV\sqrt{T\ln T})$, with$N$,$V$, and$T$denoting the numbers of stationary periods, edge devices, and time slots, respectively. Extensive simulations and testbed experiments demonstrate that CD-OSP significantly outperforms state-of-the-art baselines, which can reduce the probing cost by up to 16.18X with a 2.14X increase in the offloading delay.

Low- earth-orbit (LEO) satellite constellations (e.g., Starlink) are becoming a necessary component of future Internet. There have been increasing studies on LEO satellite networking. It is a crucial problem how to evaluate these studies in a systematic and reproducible manner. In this paper, we present OpenSN, i.e., an open source library for emulating large-scale satellite network (SN). Different from Mininet-based SN emulators (e.g., LeoEM), OpenSN adopts container-based virtualization, thus allows for running distributed routing software on each node, and can achieve horizontal scalability via flexible multi-machine extension. Compared to other container-based SN emulators (e.g., StarryNet), OpenSN streamlines the interaction with Docker command line interface and significantly reduces unnecessary operations of creating virtual links. These modifications improve emulation efficiency and vertical scalability on a single machine. Furthermore, OpenSN separates user-defined configuration from container network management via a Key-Value Database that records the necessary information for SN emulation. Such a separation architecture enhances the function extensibility. To sum up, OpenSN exhibits advantages in efficiency, scalability, and extensibility, thus is a valuable open source library that empowers research on LEO satellite networking. Experiment results show that OpenSN constructs mega-constellations 5X-10X faster than StarryNet, and updates link state 2X-4X faster than LeoEM. We also verify the scalability of OpenSN by successfully emulating the five-shell Starlink constellation with a total of 4408 satellites.

Low-earth-orbit (LEO) satellite constellations (e.g., Starlink) are becoming the necessary component of future Internet. There have been increasing studies on LEO satellite networking. It is a crucial problem how to evaluate these studies in a systematic and reproducible manner. In this paper, we present OpenSN, i.e., an open-source library for emulating large-scale satellite network (SN). Different from Mininet-based SN emulators (e.g., LeoEM), OpenSN adopts container-based virtualization, thus allows for running distributed routing software on each node, and can achieve horizontal scalability via flexible multi-machine extension. Compared to other container-based SN emulators (e.g., StarryNet), OpenSN streamlines the interaction with Docker command line interface and significantly reduces unnecessary operation of creating virtual links. These modifications improve emulation efficiency and vertical scalability on a single machine. Furthermore, OpenSN separates user-defined configuration from container network management via a key-value database that records the necessary information of SN emulation. Such a separation architecture enhances the function extensibility. To sum up, OpenSN exhibits advantages in efficiency, scalability, and extensibility, thus is a valuable open-source library that empowers research on satellite networking. Experimental results show that OpenSN can construct mage-constellations 5X-10X faster than StarryNet, and update link state 2X-4X faster than Mininet.

This work proposes a transmission scheme for a 360-degree video streaming system. A critical issue is selecting the proper parts of the images that can cover users’ viewport while simultaneously meeting bandwidth constraints. However, the imperfect prediction of real-time viewpoint and fronthaul bandwidth brings significant challenges. To address this issue, by leveraging the Lagrangian exponentially weighted average (LEWA) method, we propose a LEWA-based transmission online learning scheme that iteratively selects tiles with varying bitrates based on real-time user feedback. This approach not only ensures that Quality of Experience (QoE) approaches the static offline optimal scheme under long-term bandwidth constraints but also effectively handles bandwidth fluctuations and prediction inaccuracies through adaptive bitrate selection. A prototype for 360-degree video streaming is built. The results indicate that the proposed scheme can maintain the proportion of rebuffering time at a stable low value (less than 2.5%) and boost the bandwidth utilization by at least 13.5% and more than 50% in most testcases compared to baseline schemes.

By cutting the 360-degree video into temporal chunks and spacial tiles of different quality levels, layered 360-degree video streaming enables fine-grained bitrate adaptation. A critical challenge is whether to transmit the expected viewport at a higher quality level or pre-fetch the low-rate base layer while avoiding buffer overflow or rebuffering, given the fluctuated and constrained fronthaul bandwidth. In this work, we investigate this interplay to provision better quality of experience (QoE) while guaranteeing the smoothness of 360-degree video streaming. Specifically, an optimization problem is formulated to maximize the expected video quality under a bidirectional constraint on the long-term average buffer. To address this problem, we propose the Lyapunov Stable Point Optimization(LSPO), which is a Lyapunov optimization variant. LSPO achieves a near-optimal time-averaged QoE within an O(1/V )margin, while also upholding bidirectional buffer constraints. A buffer-based algorithm is then proposed and evaluated based on real-trace data. The results demonstrate superior performance in video quality and reduced rebuffering probability compared to existing algorithms.

The low-earth-orbit (LEO) satellite constellation is becoming the large-scale autonomous system (AS) connected to other terrestrial ASes, forming satellite-terrestrial integrated network (STIN). To reduce the latency of inter-domain content delivery, it is necessary to adopt an efficient inter-domain routing architecture in STIN. Previous studies improve the classic Border Gateway Protocol (BGP) and propose BGP-S for STIN, which proactively probes each inter-domain path. However, BGP-S suffers from a tremendous control overhead when the LEO constellation is large. In this paper, we propose a path-identified content retrieval (PCR) architecture for STIN. PCR is an information-centric architecture, and explicitly identifies the inter-domain path between neighbor ASes. Under PCR architecture, users can retrieve their desired contents by specifying the inter-domain path in the request packet. The corresponding data packets will be forwarded according to the reversed inter-domain path. This way, users could unleash the path diversity in STIN by dynamically selecting inter-domain paths according to various learning-based routing algorithms. That is, PCR achieves adaptive inter-domain content retrieval without incurring additional control overhead. We conduct extensive packet-level simulation on OMNeT++. Results show that PCR (with Exp3-SIX algorithm) outperforms state-of-the-art BGP-S in terms of content retrieval latency by 22%.

The nature of datacenter traffic is a high volume of bursty tiny flows and standing long flows, which forms the coexistence of transient and persistent congestion. Traditional congestion control (CC) algorithms have inherent limitations in reconciling fast response and high efficiency towards transients with stability and fairness during persistence. In this paper, we provide an insight that re-architects CC with two control laws, tailored to transient and persistent concerns, respectively. Armed with this key insight, we propose bimodal congestion control (BCC), which is founded on two core ideas: (i) Quaternary network state detection, which further distinguishes transient and persistent states in switches, and (ii) Bimodal control law, which is manifested as the transient controller and persistent controller at sources. The transient controller employs a precise control paradigm that pauses flows to drain backlogged packets and ramps down/up flow rates to bottleneck bandwidth directly, striving for high efficiency. The persistent controller grounds itself in traditional CC algorithms, inheriting stability and fairness. We implement BCC in the Linux kernel and P4-programmable switch. In our evaluation, compared to DCQCN, HPCC, PowerTCP, and Swift, BCC reduces flow completion times by 14% ~ 99%.

The emerging large-scale low earth orbit (LEO) constellation is expected to provide global Internet services. However, large-scale satellite networks meet the challenges of topology dynamics and continuous traffic variation. This paper proposes LoHi, a Load-aware Hierarchical Information-centric (LoHi) Routing Protocol based on constellation Partitioning and logic path identifier (PID), to address the above challenges. Specifically, LoHi divides a constellation into satellite groups and only keeps track of the inter-satellite link (ISL) state within each group instead of the entire constellation, stabilizing global routing. Moreover, LoHi adopts the PID to denote the logic connectivity of adjacent satellite groups, which corresponds to multiple physical ISLs. Accordingly, the hierarchical multipath routing is calculated based on the inner-group and inter-group connectivity information. Furthermore, LoHi adjusts forwarding decisions according to the real-time traffic load on the ISL and group-level inter-group paths to reduce packet drop and queuing delay in a hierarchical pattern. Packet-level experiment results show that LoHi achieves a higher packet delivery ratio than the state-of-the-art mechanisms (up to 132.12%).

Real-time video analytics services aim to provide users with accurate recognition results timely. However, existing studies usually fall into the dilemma between reducing delay and improving accuracy. The edge computing scenario imposes strict transmission and computation resource constraints, making balancing these conflicting metrics under dynamic network conditions difficult. In this regard, we introduce the age of processed information (AoPI) concept, which quantifies the time elapsed since the generation of the latest accurately recognized frame. AoPI depicts the integrated impact of recognition accuracy, transmission, and computation efficiency. We derive closed-form expressions for AoPI under preemptive and non-preemptive computation scheduling policies w.r.t. the transmission/computation rate and recognition accuracy of video frames. We then investigate the joint problem of edge server selection, video configuration adaptation, and bandwidth/computation resource allocation to minimize the long-term average AoPI over all cameras. We propose an online method, i.e., Lyapunov-based block coordinate descent (LBCD), to solve the problem, which decouples the original problem into two subproblems to optimize the video configuration/resource allocation and edge server selection strategy separately. We prove that LBCD achieves asymptotically optimal performance. According to the testbed experiments and simulation results, LBCD reduces the average AoPI by up to 10.94X compared to state-of-the-art baselines.

Efficient and scalable networking is a key enabler of the Unmanned Aerial Vehicle (UAV) swarms, wherein multiple UAVs cooperatively execute complicated tasks. Despite the intermittent connections due to the UAV mobility, stable paths may exist temporally in periods like formation keeping, which is rarely considered or utilized in existing UAV routing designs. In this article, we propose an integrated host- and content-centric routing (IHCR) mechanism to harness the advantages of both routing mechanisms. Specifically, the routing information of stable paths is reused in a host-centric manner to reduce the flooding for path exploring. In addition, the route failure detection and re-routing are content-centric to adjust to the topology dynamics. The challenges lie in the inherent contradiction between host-centric and content-centric routing mechanisms (e.g., naming spaces) and the tradeoff between path reusing and re-routing. To overcome these challenges, we appropriately incorporate node names into content names and then fully exploit reusable paths via time-based route failure detection and delayed forwarding. Packet-level simulation results show that IHCR increases the packet delivery ratio by 60.1%, and enlarges the achievable network scale by 4.2 times compared to state-of-the-art routing mechanisms.

RoCEv2 (RDMA over Converged Ethernet version 2) is the canonical method for deploying RDMA in Ethernet-based datacenters. Traditionally, RoCEv2 runs over the lossless network which is in turn achieved by enabling Priority Flow Control (PFC) within the network. However, as the scale of the datacenter increases, PFC’s side effects, such as head-of-line blocking, congestion spreading, and pause frame storm, are amplified. Datacenter operators can no longer tolerate these problems. In hence, they are seeking PFC alternatives for RDMA networks. Rather than aiming at the lossless RDMA network, we instead handle packet loss effectively to support RDMA over Ethernet. In this paper, we propose Switch-assistant Loss Recovery (SLR), a switch building block to enhance RoCEv2’s loss recovery. Specifically, SLR-enabled switches send loss notifications to request fast retransmissions. To cooperate with go-back-N retransmission, SLR generates loss notifications only when expected packets (i.e., in-order packets expected by receivers) are dropped and then filters out unexpected packets, which can avoid timeouts and prevent exacerbating congestion. Further, we adapt SLR to multi-bottleneck scenarios by inferring expected packets among multiple switch views. We implement SLR prototypes on commodity programmable switches. Evaluations show that SLR reduces the 99.9th-percentile FCT slowdown by up to 21.6$\times$compared to PFC and other state-of-the-arts.

Low-Earth-Orbit (LEO) satellite constellations are becoming the necessary infrastructure in the future. However, the secure operation of LEO constellations is faced with severe risks. Specifically, LEO satellites are constantly orbiting and their channel interfaces are open. The adversary in hostile regions can leverage the global footprint to inject malicious traffic via access satellites. That is, LEO satellites are susceptible to physical and cyber attacks. Therefore, access authentication regarding terrestrial users (TUs) is crucial to ensure the secure operation of LEO constellations. The traditional on-orbit authentication frameworks usually presume that satellites are reliable and mutually trusted, thus one could rely on access satellites to perform authentication. In practice, however, physical and cyber attacks could bring down the satellites (causing fail-stop fault) or even hijack the satellites (causing Byzantine fault). This fact requires that the access authentication framework installed on LEO constellations should be fault-tolerant. In this paper, we aim to achieve Byzantine fault tolerance in access authentication for LEO satellite networks by properly integrating PBFT consensus protocol with traditional on-orbit authentication. Based on the topology characteristics of LEO constellations, we analytically derive the consensus probability, authentication accuracy, and communication overhead under PBFT-based authentication. To reduce the communication overhead, we propose to partition the constellation into multiple consensus groups, and devise a hierarchical PBFT (HPBFT) protocol. Simulation results based on Starlink Shell-I constellation indicate that HPBFT-based authentication could reduce the communication overhead (by an order of magnitude) and maintain almost the same authentication accuracy compared to PBFT-based authentication.

Real-time video analytics services are expected to deliver accurate recognition results to users timely. However, existing studies usually fail in the dilemma between reducing delay and improving accuracy. Balancing such conflicting metrics is extremely hard under dynamic network conditions. In this regard, we introduce the age of processed information (AoPI) concept, i.e., the time elapsed since the generation of the latest accurately recognized frame. As a systematic metric, AoPI depicts the integrated impact of recognition accuracy, transmission, and computation efficiency. We derive the closed-form expressions of AoPI under preemptive and non-preemptive computation scheduling policies w.r.t. the transmission/computation rate and recognition accuracy of video frames, which are validated using prototype experiments. Based on the derived results, we study the joint video configuration selection, bandwidth, and computation resource allocation problem to minimize the long-term average AoPI among all cameras. An efficient method is proposed to solve the problem, which utilizes Lyapunov optimization and block coordinate descent to make decisions online without requiring future information about network variations and video content. We prove that our method achieves asymptotically optimal performance. Extensive simulations show that our method reduces the AoPI by up to 4.06X compared with the state-of-the-art baselines.

Many Internet platforms collect fresh information of various points of interest (PoIs) relying on users who happen to be nearby the PoIs. The platform will offer reward to incentivize users and compensate their costs incurred from information acquisition. In practice, the user cost (and its distribution) is hidden to the platform, thus it is challenging to determine the optimal reward. In this paper, we investigate how the platform dynamically rewards the users, aiming to jointly reduce the age of information (AoI) and the operational expenditure (OpEx). Due to the hidden cost distribution, this is an online non-convex learning problem with partial feedback. To overcome the challenge, we first design an age-based rewarding scheme, which decouples the OpEx from the unknown cost distribution and enables the platform to accurately control its OpEx. We then take advantage of the age-based rewarding scheme and propose an exponentially discretizing and learning (EDAL) policy for platform operation. We prove that the EDAL policy performs asymptotically as well as the optimal decision (derived based on the cost distribution). Simulation results show that the age-based rewarding scheme protects the platform’s OpEx from the influence of the user characteristics, and verify the asymptotic optimality of the EDAL policy.

Low earth orbit (LEO) satellite networks have the potential to provide low-latency communication with global coverage. To unleash this potential, it is crucial to achieve efficient data delivery. In this paper, we analyze the topology characteristics of LEO satellite networks, and propose a source-route-style forwarding framework. Specifically, we leverage the deterministic neighbor relationship and identify all the unidi-rectional inter-satellite links (ISLs). Moreover, our framework utilizes the in-packet bloom filter (BF) to store the source-route-style forwarding information. This way, the source satellite could encode multiple ISL identifiers into the BF, which actually specifies the forwarding path. The intermediate satellites only need to check whether the outgoing ISLs are encoded and forward packets accordingly. Due to false positives caused by BF, the more ISLs are encoded at a time, the more redundant forwardings emerge. To reduce forwarding overhead, we take into account segment encoding, allowing the source and intermediate satellites to encode part of ISLs towards the destination. Overall, segment encoding seeks the right balance between forwarding overhead and encoding delay. We characterize a wide range of segment encoding policy in a unified framework, and derive the expected forwarding overhead in a closed-form. The segment encoding design is formulated as a binary non-linear programming, which is NP-hard. To overcome the challenge, we leverage its decomposable structure, and propose an efficient algorithm to solve it optimally. Finally, we validate our analytical results via packet-level experiments. Results also show that our proposed segment encoding policy significantly reduces the queuing delay compared to source encoding.

Accommodating services at the network edge is favorable for time-sensitive applications. However, maintaining service usability is resource consuming in terms of pulling service images to the edge, synchronizing databases of service containers, and hot updates of service modules. Accordingly, it is critical to determine which service to place based on the received user requests and service refreshing (maintaining) cost, which is usually neglected in existing studies. In this work, we study how to cooperatively place timely refreshing services and offload user requests among edge servers to minimize the backhaul transmission costs. We formulate an integer nonlinear programming problem and prove its NP-hardness. This problem is highly nontractable due to the complex spatial-and-temporal coupling effect among service placement, offloading, and refreshing costs. We first decouple the problem in the temporal domain by transforming it into a Markov shortest path problem. We then propose a lightweighted discounted value approximation (DVA) method, which further decouples the problem in the spatial domain by estimating the offloading costs among edge servers. The worst performance of DVA is proved to be bounded. 5G service placement testbed experiments and real-trace simulations show that DVA reduces the total transmission cost by up to 59.1% compared with the state-of-the-art baselines.

In this work, we aim to maintain the timeliness of a multipath-based real-time video analytics system by analyzing the age of processed information (AoPI) at the receiver side. In the system, a camera consistently uploads captured frames to different edge servers for processing via corresponding wireless channels. To measure the timeliness of the system, a novel metric named AoPI is proposed, which is the time elapsed since the generation of the latest successfully recognized frame. Hence, AoPI is impacted by the transmission/computation delay on different paths and whether the frames are successfully recognized. We derive the closed-form average AoPI at the receiver side of the system, which is inversely proportional to the recognition probability. Moreover, we prove that adding an identical path can reduce the average AoPI by 37.5% to 50% compared with using a single path. Nevertheless, numerical results show that utilizing a secondary path to access an available edge node will increase the average AoPI in the case of low spectrum efficiency and constrained bandwidth.

In this paper, the content service provision of information-centric vehicular networks (ICVNs) is investigated from the aspect of mobile edge caching, considering the dynamic driving-related context information. To provide up-to-date information with low latency, two schemes are designed for cache update and content delivery at the roadside units (RSUs). The roadside unit centric (RSUC) scheme decouples cache update and content delivery through bandwidth splitting, where the cached content items are updated regularly in a round-robin manner. The request adaptive (ReA) scheme updates the cached content items upon user requests with certain probabilities. The performance of both proposed schemes are analyzed, whereby the average age of information (AoI) and service latency are derived in closed forms. Surprisingly, the AoI-latency trade-off does not always exist, and frequent cache update can degrade both performances. Thus, the RSUC and ReA schemes are further optimized to balance the AoI and latency. Extensive simulations are conducted on SUMO and OMNeT++ simulators, and the results show that the proposed schemes can reduce service latency by up to 80 percent while guaranteeing content freshness in heavily loaded ICVNs.

Distributed denial of service (DDoS) flooding attacks are very harmful and difficult to prevent due to the default-on nature of both inter-domain and intra-domain routing adopted by the current Internet. Accordingly, many future Internet initiatives try to eliminate DDoS attacks by design. Among these efforts, using path identifiers (PIDs) as inter-domain routing objects has attracted much research interest. However, existing approaches either advertise PIDs throughout the Internet or use secret but forgeable (whether static or dynamic) PIDs, which makes it easy to launch DDoS flooding attacks. To address this issue, in this paper we propose K-PID that uses cryptographic (thus unforgeable) PIDs as inter-domain routing objects. In particular, an${N}$-bit PID is comprised of an${n}$-bit prefix and (${N}\,\,-\,\,{n}$) bits that are cryptographic hash over per-flow/request information and a secret number. The prefix is used for inter-domain packet forwarding and the cryptographic hash is used as a token for allowing a data packet to enter into (or, pass through) a domain. We analyze K-PID’s performance in preventing DDoS flooding attacks and implement K-PID in a prototype to verify K-PID’s feasibility. The results show that K-PID can effectively prevent DDoS flooding attacks at a low cost of reducing the forwarding capability of routers.

Mobile edge caching can effectively reduce service delay but may introduce information staleness, calling for timely content refreshing. However, content refreshing consumes additional transmission resources and may degrade the delay performance of mobile systems. In this work, we propose a freshness-aware refreshing scheme to balance the service delay and content freshness measured by Age of Information (AoI). Specifically, the cached content items will be refreshed to the up-to-date version upon user requests if the AoI exceeds a certain threshold (named as refreshing window). The average AoI and service delay are derived in closed forms approximately, which reveals an AoI-delay tradeoff relationship with respect to the refreshing window. In addition, the refreshing window is optimized to minimize the average delay while meeting the AoI requirements, and the results indicate to set a smaller refreshing window for the popular content items. Extensive simulations are conducted on the OMNeT++ platform to validate the analytical results. The results indicate that the proposed scheme can restrain frequent refreshing as the request arrival rate increases, whereby the average delay can be reduced by around 80% while maintaining the AoI below one second in heavily-loaded scenarios.

Vehicular networks are expected to support diverse content applications with multi-dimensional quality of service (QoS) requirements, which cannot be realized by the conventional one-fit-all network management method. In this paper, a service-oriented hierarchical soft slicing framework is proposed for the cache-enabled vehicular networks, where each slice supports one service and the resources are logically isolated but opportunistically reused to exploit the multiplexing gain. The performance of the proposed framework is studied in an analytical way considering two typical on-road content services, i.e., the time-critical driving related context information service (CIS) and the bandwidth-consuming infotainment service (IS). Two network slices are constructed to support the CIS and IS, respectively, where the resource is opportunistic reused at both intra- and inter-slice levels. Specifically, the throughput of the IS slice, the content freshness (i.e., age of information) and delay performances of the CIS slice are analyzed theoretically, whereby the multiplexing gain of soft slicing is obtained. Extensive simulations are conducted on the OMNeT++ and MATLAB platforms to validate the analytical results. Numerical results show that the proposed soft slicing method can enhance the IS throughput by 30% while guaranteeing the same level of CIS content freshness and service delay.

Mobile edge caching is an effective way to reduce the service delay of content delivery, where the popular contents can be pro-actively stored in proximity to users. In practice, the cached contents should be updated timely to avoid information staleness, in case that the information of a content changes with time and environment. However, cache update consumes additional transmission resources, which can degrade the delay performance. This work studies the fundamental tradeoff relationship between the content freshness (depicted by the age of information (AoI)) and service delay in mobile edge caching networks, and proposes a freshness-aware cache update scheme to achieve the AoI-delay balance. In specific, the base station will fetch the latest version of a content before delivery, if the AoI is larger than a certain threshold (i.e., update window size). The average AoI and service delay are derived in closed forms through approximated analysis of queueing systems, revealing a tradeoff relationship with respect to the update window size. Extensive simulations are conducted on the OMNeT++ platform, which validates the analytical results. Both the analytical and simulation results show that the proposed scheme can flexibly balance the average AoI and delay on demand, by tuning the update window size. Furthermore, the proposed scheme can also avoid frequent update in case of heavy content requests, whereby the AoI and delay are regulated by setting the appropriate update window size.

The fifth-generation (5G) network cloudification enables third parties to deploy their applications (e.g., edge caching and edge computing) at the network edge. Many previous works have focused on specific service strategies (e.g., cache placement strategy and vCPU provision strategy) for edge applications from the perspective of a certain third party by maximizing its benefit. However, there is no literature that focuses on how to efficiently allocate resources from the perspective of a mobile network operator, taking the different deployment requirements of all third parties into consideration. In this paper, we address the problem by formulating an optimization problem, which minimizes the total deployment cost of all third parties. To capture the deployment requirements of the third parties, the applications that they want to deploy are classified into two types, namely, computation-intensive ones and storage-intensive ones, whose requirements are considered as input parameters or constraints in the optimization. Due to the NP-hardness and non-convexity of the formulated problem, we have designed an elitist genetic algorithm that converges to the global optimum to solve it. Extensive simulations have been conducted to illustrate the feasibility and effectiveness of the proposed algorithm.

Time-dependent pricing (TDP) sets different prices in different time slots in order to motivate users to shift their delay-tolerant flows from congested time slots to less congested ones, thus helping Internet service providers (ISPs) utilize their network capacity more efficiently. In existing TDP approaches, however, once a flow is delayed to a less congested time slot by a user, the user has to wait until that time slot to consume the flow, even if there is idle capacity in earlier time slot(s) to accommodate the flow. In addition, in case that the traffic usage shifted to some time slots is so aggressive that new congestion is caused, it is hard for the ISP to accommodate more bursty traffic. To address these issues, in this paper we propose an approach to pre-schedule the delayed flows before their deadlines. Our results from extensive simulations show that the proposed approach could benefit both users and ISPs. For example, an ISP can smooth its bandwidth usage, which in turn makes it possible to accommodate more bursty traffic.

Information-Centric Networking (ICN) is a promising network paradigm for the future Internet. As in the current Internet, selfish routing is also crucial problem in ICN. To the best of our knowledge, however, the selfish routing problem in ICN is remaining an unresolved challenge. To fill this gap, in this paper we propose a Nash Bargaining based content registration (NBREG) method, which is used for register content names (dissemination of content reachability information) from the game theoretic perspective. NBREG allows neighboring domains to cooperate with each other without revealing their internal private information. Based on results from real (inter-domain topology) trace simulations and prototype implementations, we show that neighboring domains can obtain more benefits with NBREG than they register and forward contents selfishly.

The multipath transmission scheme in vehicular networks has become a hot topic. It is a great challenge to overcome the unreliability of wireless network in multipath transmission. Recently, scholars propose a lot of network coding schemes to solve this problem. These schemes implement network coding algorithms by bitwise X O R or Galois Field arithmetic. However, these schemes cannot take into account both coding flexibility and computational complexity. Therefore, we propose a BigNum Network Coding (BNNC) scheme. The core idea of the BNNC scheme is to treat a packet as an integer and implement the network coding through linear operations on the integer set. It replaces bitwise XOR and Galois Field arithmetic with integer arithmetic that guarantees high coding flexibility and low computational complexity. In this paper, first, we propose the BNN C scheme that can effectively improve the reliability of multipath transmission in vehicular networks with lower computational complexity than current network coding scheme. Second, we design the Independent Matrix that enables the coding process to improve coding efficiency without independent check. Third, we compare BNNC scheme with Earliest Completion First (ECF) and Galois Field network coding scheme through a lot of simulations and real tests. The results show that the BNN C scheme is significantly superior to the Galois Field network coding schemes in terms of computational performance. And in terms of the network performance, the BNNC scheme can overcome the unreliability of links in multipath transmission.

The existing satellite communication systems suffer from traditional design, such as slow configuration, inflexible traffic engineering, and coarse-grained Quality of Service (QoS) guarantee. To address these issues, in this paper, we propose SERvICE, a Software dEfined fRamework for Integrated spaCe-tErrestrial satellite Communication, based on Software Defined Network (SDN) and Network Function Virtualization (NFV). We first introduce the three planes of SERvICE, Management Plane, Control Plane, and Forwarding Plane. The framework is designed to achieve flexible satellite network traffic engineering and fine-grained QoS guarantee. We analyze the agility of the space component of SERvICE. Then, we give a description of the implementation of the prototype with the help of the Delay Tolerant Network (DTN) and OpenFlow. We conduct two experiments to validate the feasibility of SERvICE and the functionality of the prototype. In addition, we propose two heuristic algorithms, namely the QoS-oriented Satellite Routing (QSR) algorithm and the QoS-oriented Bandwidth Allocation (QBA) algorithm, to guarantee the QoS requirement of multiple users. The algorithms are also evaluated in the prototype. The experimental results show the efficiency of the proposed algorithms in terms of file transmission delay and transmission rate.

In recent years, there are increasing interests in using path identifiers (PIDs) as inter-domain routing objects in the future Internet. While PIDs are advertised throughout the Internet in some future Internet architectures, they are kept secret in others. In this paper, we investigate the benefits, from the perspective of preventing distributed denial-of-service (DDoS) attacks, of keeping PIDs secret in future Internet when compared with advertising them throughout the Internet. Our results from extensive simulations show that keeping PIDs secret significantly helps prevent DDoS attacks.

Greater demands are being placed on the access bandwidth, stability, and delay of network because of the quickening rhythm of life and work, especially in mobile scenario. In order to obtain a stable network with low latency and high bandwidth in mobile scenario, taking advantage of the wireless heterogeneous network in parallel is a good choice. Nowadays, people are increasingly concerned about the network quality under the mobile scenario. Some scholars have done the relevant measurements. However, all of those measurements mainly investigate part of the network parameters or part of mobile scenarios. In this paper, we make the following contributions. Firstly, in high‐speed mobile scenario, the wireless network qualities of different vendors are measured synthetically. Secondly, we analyze the benefits of taking advantage of the different vendors. Thirdly, we deploy the replication link mechanism in high‐speed mobile scenario and propose an algorithm to remove the duplicate packet in high‐speed mobile scenario. And the algorithm can also be used in another multipath schedule algorithm to improve the reliability.

Existing satellite communication has a low efficiency due to the inherent defects of the traditional design, i.e., coarsegrained control, and long configuration delay. In some previous work, researchers developed Software Defined Satellite Networks (SDSN). We reconsidered many characteristics equipped in satellite links, and deployed SDSN in the prototype by leveraging Delay Tolerant Network (DTN) and OpenFlow. However, it is necessary to develop a theoretical tool for this new network architecture to evaluate its performance. In this paper, we propose such an analytical model for SDSN using the queueing model. In particular, the Jackson's theorem is adopted to model the communication between a controller and forwarding nodes, and the store-and-forward process. The comparisons between the numerical and experimental results indicate that the proposed model is able to accurately evaluate the performance of SDSN, and will provide great benefits for the further related researches.

In recent years, there are increasing interests in using path identifiers (PIDs) as inter-domain routing objects. However, the PIDs used in existing approaches are static, which makes it easy for attackers to launch the distributed denial-ofservice (DDoS) flooding attacks. To address this issue, in this paper, we present the design, implementation, and evaluation of dynamic PID (D-PID), a framework that uses PIDs negotiated between the neighboring domains as inter-domain routing objects. In D-PID, the PID of an inter-domain path connecting the two domains is kept secret and changes dynamically. We describe in detail how neighboring domains negotiate PIDs and how to maintain ongoing communications when PIDs change. We build a 42-node prototype comprised of six domains to verify D-PID's feasibility and conduct extensive simulations to evaluate its effectiveness and cost. The results from both simulations and experiments show that D-PID can effectively prevent DDoS attacks.

Providing enhanced security is an important design objective of many future Internet architectures. In this paper, we propose a dynamic path identifier (D-PID) mechanism for a recently proposed future Internet architecture called CoLoR. The D-PID mechanism can efficiently enhance the security of the network by periodically changing the path identifiers (PIDs) between domains, which are used for inter-domain routing in CoLoR. We describe the D-PID mechanism in detail, and simulate it in OMnet++ to verify its effectiveness. Our evaluation results show that the extra network overhead caused by D-PID is controllable and trivial.

To enhance seamless provider mobility support in NDN, we propose a Novel Locator Based mobility support Approach (NLBA). In this approach, we assign an unique locator to each Access Router (AR) in NDN networks, and further modify the outgoing faces field in AR's original Forwarding Information Base (FIB), to record the mobility status and the current locator of the provider. Besides, we append an optional field to the original NDN packet, and further extend the AR with additional functionalities, such as caching or forwarding Interest packets on behalf of the provider. Our analytical investigations indicate that NLBA has lower handover cost and shorter handover latency, compared with other existing rendezvous/indirection point based mobility support approach.

Information-centric networking (ICN) and software defined networking (SDN) are two novel network paradigms that the networking community is actively investigating. Because of their salient features, there are increasing attempts to integrate ICN and SDN. In this paper, we show how a recently proposed future Internet architecture (called CoLoR) makes it efficient to integrate SDN and ICN. In particular, we show how CoLoR reduces the flow setup delay, the number of flow setup requests, and the number of flow entries.

Recently there has been a new emerging trend in integrating Information Centric Networking (ICN) and Software Defined Networking (SDN) together in the future internet research area. Software defined information centric networking (SD-ICN) may face more serious scalability problem in control plane compared with traditional SDN environment due to new features about in-network cache and content-based communication. In this paper, we address the control plane scalability problem from viewpoint of ICN/SDN integration and propose a scalable area-based hierarchical architecture (SAHA) for controller deployment in SD-ICN. The SAHA supports scalable awareness of network resources and content resources, as well as guarantees efficient interest matching and resource adaptation. Simulation experiments under OMNET++ show that the proposed SAHA can achieve good scalability in resource awareness and content-based communication.

Software-defined networking (SDN) has attracted many research interests among the networking community and has been deployed in many small to moderate networks. Although many approaches have been proposed to address the scalability issue of SDN, however, it is still an open problem whether SDN can be applied to large scale networks such as Tier-1 Internet service providers (ISP) when it works in passive mode. To address this problem, we in this paper analyze the number of flow entries that a switch needs to maintain and the number of flow setup requests per second that a controller needs to deal with, based on real data traces collected from a link between two routers in a Tier-1 ISP. The results show that, if we store a unique flow entry for every flow, SDN cannot be applied to large ISPs. In addition, if switches are required to deal with 12-tuple flow entries, SDN still cannot be applied to large Tier-1 ISPs even if we only setup unique flow entries for flows whose sizes are larger than 100 MB. However, if switches are required to deal with only 2-tuple flow entries, SDN can be applied to large Tier-1 ISPs if we only setup unique flow entries for flows whose sizes are larger than 10 MB.

The original architecture of content-centric network CCN may suffer from interest flooding attacks. In this paper, we focus on one type of interest flooding attacks called denial of service against content source DACS attack. To damage CCN, it floods a large number of malicious interests requesting content that does not exist, which guarantees that no cache hit can occur at routers until these malicious interests reach the target content source. Thus, it can directly exhaust the resource of the victim. To counter it, we propose a threshold-based detecting and mitigating TDM scheme. The basic idea is to detect DACS attack on the basis of the frequency that pending interest table items in CCN routers expire recording this frequency by introducing two counters with their corresponding thresholds and one indicator for counter mode and to mitigate it by implementing the rate limiter in each router. From the viewpoint of a CCN router, we analyze the performance of TDM in terms of detection ability and effect on mitigating malicious traffic. In addition, we briefly analyze the overhead of TDM. The results show that TDM achieves high detection ability and good effect on mitigating malicious traffic while bringing in small overhead on countering DACS attack. To the best of our knowledge, this is the first attempt to design a detailed scheme embedded with corresponding algorithms on countering this attack. Copyright © 2013 John Wiley & Sons, Ltd.

In this paper, we analyze the security threats of a newly proposed future Internet architecture called CoLoR. In particular, we describe how CoLoR defends against the most prevalent attacks existing in both the current Internet and some recently proposed information-centric networks such as named data networking (NDN). We also present attacks that are specific to CoLoR and discuss how to deal with them. Through our analysis, we find that CoLoR is more secure than both the current Internet and NDN.

The locator/ID separation protocol (LISP) proposed for addressing the scalability issue of the current Internet has gained much interest. LISP separates the identifier and locator roles of IP addresses by end point identifiers (EIDs) and locators, respectively. In particular, while EIDs are used in the application and transport layers for identifying nodes, locators are used in the network layer for locating nodes in the network topology. In LISP, packets are tunneled from ingress tunnel routers (ITRs) to egress tunnel routers in a map-and-encapsulation manner. For this purpose, an ITR caches on demand some mappings between EIDs and locators. Since hosts roam from place to place, however, their EID-to-locator mappings change accordingly. Thus, an ITR cannot store a mapping permanently but maintains for every mapping a timer whose default value is set to a given cache timeout. If the cache timeout for a mapping is too short, an ITR frequently queries the mapping system (control plane), resulting in a high traffic load on the control plane. On the other hand, if the cache timeout for a mapping is too long, the mapping could be outdated, resulting in packet loss and associated overheads. Therefore, it is desirable to set appropriate cache timeout for mapping items. In this paper, we analytically determine the optimal cache timeout for EID-to-locator mappings cached at ITRs to minimize the control plane load while remaining efficient for mobility. The results presented here provide valuable insights and guidelines for deploying LISP.

As a promising network-based mobility management method that does not require active participation of mobile nodes (MNs), Proxy Mobile IPv6 (PMIPv6) is attracting considerable attention among the telecommunication and Internet communities. It remains an open issue how to build a scalable PMIPv6 domain that is able to support a large number of MNs while keeping handover delays low. In this paper, we propose an approach for building Scalable And Robust PMIPv6 (SARP) domains. We propose that every mobility access gateway (MAG) in a SARP domain also functions as a local mobility anchor (LMA), and is organized into a virtual ring with all other MAGs. Consistent hashing is used to efficiently distribute the mapping between each MN and its LMA to all MAGs. A MAG finds an MN's LMA by sending a query message to the virtual ring. Our analysis verifies the robustness and scalability of SARP. We also propose two handover procedures for SARP and show that they achieve low handover delays.

Mobile multicast becomes a research hotspot with the development of wireless and mobile technologies, and it is based on the traditional multicast protocols and mobility management protocols to provide the multicast services for mobile subscribers. Several mobile multicast methods were proposed in the past few years, but most of them are based on the mobile IPv6 and its alternatives which require the mobile hosts to support the mobility function. Recently, the proxy mobile IPv6 (PMIPv6) was proposed to provide the mobility support for mobile node with or without mobility involvement, and the previous studies have shown that the PMIPv6 can improve the handover performance. However, the PMIPv6 mainly concerns on the unicast routing support and little considers the multicast routing. In this paper, we study the multicast support in PMIPv6 and propose two multicast methods called the MAG (mobile access gateway)-based method and LMA (local mobility anchor)-based method, and analyze their performance under different scenarios. The analytical results show that the LMA-based method is suitable for the bigger PMIPv6 domain, and larger network topology scenarios (more than 105), whereas the MAG-based method is used for the smaller PMIPv6 domain.

Because of its salient features such as ease of deployment, Proxy Mobile IPv6 (PMIPv6) is a promising solution for mobility management and is attracting considerable attention among the telecommunication and Internet communities. To the best of our knowledge, however, it is still an open issue how to build a scalable PMIPv6 domain so that a PMIPv6 domain is able to support as many mobile nodes (MNs) as possible while keeping low handover delay. In this paper, we propose an approach for building Scalable And Robust PMIPv6 (SARP) domains. We propose that every mobile access gateway (MAG) behaves as both an MAG and a local mobility anchor (LMA). All MAGs in a proxy mobility domain then organize into a ring and (key = MN-identifier, value = MN's LMA) pairs are distributed to all MAGs using consistent hashing. In this way, every MAG can send proxy binding update messages to the LMA identified by hashing the MN-identifier of the MN. We show that SARP is robust, scalable, and has very low handover delay. In particular, our results show that with SARP, a single PMIPv6 domain is able to support 108MNs.

It is commonly recognized that today's Internet routing and addressing system is facing serious scaling problems, which are mainly caused by the overloading of IP address semantics. That is, an IP address represents not only the location but also the identity of a host. To address this problem, several recent schemes propose to replace the IP namespace in today's Internet with a locator namespace and an identity namespace. The locator namespace consists of locators that are used to represent the locations of hosts. On the other hand, the identity namespace consists of identifiers that are used to represent the identities of hosts. For these schemes to work, there must be a mapping system that can supply an appropriate locator for any given end point identifier (EID). While prior related works mainly focus on aggregable EIDs, several recent works proposed the use of self-certifying EIDs for purpose of security and privacy. However, self-certifying EIDs are flat, unstructured and prior proposals cannot be used to deal with flat EIDs. In this paper, we propose a Distributed hash table (DHT)-based identifier-to-locator mapping scheme to resolve a locator for a flat identifier. We evaluate the performance of the proposed scheme. We show that, besides the capability to support flat EIDs, the scheme has good scalability and low resolution delay. We also show that the scheme is robust and can efficiently support mobility.

The Border Gateway Protocol (BGP) is the only inter-domain routing protocol currently. BGP allows ASes to select and propagate routes based on flexible and locally defined policies. But the flexibility and freedom of policies can lead to routing instability, even policy disputes among ASes cause inter- domain routing oscillations. Recent studies either enforce global constraints on policies without freedom and privacy, or require expensive memory consumption and huge message overhead. In this paper, we propose a solution that operates with small overhead, guarantees safe convergence, and preserves policy freedom and privacy as much as possible. It uses a distributed mechanism for detecting and solving policy disputes at run time. Only when the policy-induced oscillations exist, ASes suppress the dispute routes for safety.

It has been widely recognized in the literature that it is imperative to protect light-tree based multicast sessions against single link failures since a single fiber failure can disrupt the information dissemination to several destination nodes. In this paper, we address the problem of routing survivable multicast sessions (RSMS) in wavelength-division multiplexing (WDM) mesh networks. We consider the dynamic network environment, where multicast sessions arrive dynamically one after another. Our objective is to be able to consume as least cost (e.g., wavelengths) as possible for one-at-a-time arrivals and no priori knowledge of future arrivals. We present an approximation algorithm that outperforms previously proposed algorithms for the RSMS problem such as optimal path-pair-based shared disjoint paths (OPPSDP). To the best of our knowledge, this is the first approximation algorithm proposed for the RSMS problem. We prove that the cost of the solution obtained by the HCBA algorithm is at most 4 times that of the optimal solution. We show by simulation that our algorithm performs very close to the optimal solution obtained by solving a mathematical formulation for the RSMS problem. We also show that, compared with the OPPSDP algorithm, our algorithm can significantly reduce the average cost and the blocking probability.

The advances in wavelength-division multiplexing (WDM) technology are expected to facilitate bandwidth-intensive multicast applications. A single fiber failure in such a network, however, can disrupt the information dissemination to several destination nodes in a "Iight-tree"-based multicast session. Thus it is imperative to protect the multicast sessions. In this paper, we propose a novel protection scheme, called multicast protection through spanning paths (MPSP), for resource efficient multicast protection with spare capacity sharing. Here, a spanning path is a path from a leaf node to any other leaf node of a multicast tree. The key idea of MPSP is first to identify a backup path for each spanning path and then to appropriately select parts of these backup paths to protect the primary multicast tree, so that the total bandwidth allocated to the primary multicast tree and its protection paths (or trees, etc.) is minimized. While previous studies only consider self-sharing and intra-request sharing, to the best of our knowledge, this is the first time to take inter-request sharing of spare capacity into consideration when protecting dynamic multicast sessions. We use simulations to demonstrate the performance of the MPSP scheme. It is shown that significant performance improvements are achieved in terms of average cost per multicast session and blocking probability. Compared with existing schemes, the average cost is reduced by about 22% and the blocking probability can be reduced by about 27% in average.

Segment protection has been recognized as an efficient way to avoid ldquotrapsrdquo in survivable WDM mesh network. In this paper, we present some insights on this kind of protection. We first prove the correctness of segment protection used for avoiding traps. We then investigate the effect of the number of segments on the blocking performance in several typical real networks (includes middle and large networks). We find that, in most cases, it is sufficient to use two backup segments to protect a given active path. Based on this observation, we then propose a novel and efficient segment protection algorithm, called two-segment (TS), which has a lower computational complexity and comparative performance than existing algorithms.

The advances in wavelength-division multiplexing (WDM) technology are expected to facilitate bandwidth-intensive multicast applications. A single fiber cut on such a network, however, can disrupt the transmission of information to several destination nodes on a "light-tree"- based multicast session. Thus it is imperative to protect multicast sessions. In this article we propose a novel protection scheme called multicast protection through spanning paths (MPSP) for efficient multicast protection. Here, a spanning path is a path from a leaf node to any other leaf node of a multicast tree. The key idea of MPSP is to derive a backup path for each spanning path and then appropriately select part of these backup paths to protect the primary multicast tree such that the total bandwidth allocated to the primary multicast session and its protection paths (or trees, etc.) for all the multicast sessions is minimized. Simulation results are used to demonstrate the good performance of the proposed protection scheme in reducing the spare capacity for protection. Compared with existing schemes, the decrease in average cost can be quite high (e.g., decrease about 20%) and the blocking probability can be reduced approximately 15%.