This paper studies a problem of jointly optimizing two important operations in mobile edge computing without knowing future requests, namely service caching, which deter-mines which services to be hosted at the edge, and service routing, which determines which requests to be processed locally at the edge. We aim to address several practical challenges, including limited storage and computation capacities of edge servers and unknown future request arrival patterns. To this end, we formulate the problem as an online optimization problem, in which the objective function includes costs of forwarding requests, processing requests, and reconfiguring edge servers. By leveraging a natural timescale separation between service routing and service caching, namely, the former happens faster than the latter, we propose an online two-stage algorithm and its randomized variant. Both algorithms have low complexity, and our fractional solution achieves sublinear regret. Simulation results show that our algorithms significantly outperform other state-of-the-art online policies.

While the IoT market continues to grow, securing IoT systems remains a challenge as successful cyberattacks keep escalating. Named Data Networking (NDN) offers a number of advantages over traditional IP-based communications and is considered a promising candidate to revolutionize the IoT space, thanks to its improved scalability and built-in security features. A cornerstone of any NDN IoT network is the onboarding protocol, whose main goal is to bootstrap the cryptographic keys and trust relationships necessary for a newly joining device to securely communicate with the rest of the network. Though several such protocols have been proposed, none so far combines strong security guarantees with ease of use on IoT devices that have highly constrained input/output interfaces. In this paper we introduce a novel password-based onboarding protocol to address this need. In addition to discussing its design, we produce a formalization of the protocol and verify its security properties using an automated analyzer. Finally, we present the results of benchmarking carried out on a proof-of-concept implementation that demonstrates the feasibility of our approach.

The 5G research community is increasingly leveraging the innovative features offered by Information Centric Networking (ICN). However, ICN’s fundamental features, such as in-network caching, make access control enforcement more challenging in an ICN-based 5G deployment. To address this shortcoming, we propose a Blockchain-based Decentralized Authentication Protocol (BDAP) which enables efficient and secure mobile user authentication in an ICN-based 5G network. We show that BDAP is robust against a variety of attacks to which mobile networks and blockchains are particularly vulnerable. Moreover, a preliminary performance analysis suggests that BDAP can reduce the authentication delay compared to the standard 5G authentication protocols.

Infrastructure-as-a-Service cloud providers sell virtual machines that are only specified in terms of number of CPU cores, amount of memory, and I/O throughput. Performance-critical aspects such as cache sizes and memory latency are missing or reported in ways that make them hard to compare across cloud providers. It is difficult for users to adapt their application’s behavior to the available resources. In this work, we aim to increase the visibility that cloud users have into shared resources on public clouds. Specifically, we present CacheInspector , a lightweight runtime that determines the performance and allocated capacity of shared caches on multi-tenant public clouds. We validate CacheInspector ’s accuracy in a controlled environment, and use it to study the characteristics and variability of cache resources in the cloud, across time, instances, availability regions, and cloud providers. We show that CacheInspector ’s output allows cloud users to tailor their application’s behavior, including their output quality, to avoid suboptimal performance when resources are scarce.

The Internet can be made more efficient and robust with hop-by-hop multipath routing: Each router on the path can split packets between multiple nexthops in order to 1) avoid failed links and 2) reduce traffic on congested links. Before deciding how to split traffic, one first needs to decide which nexthops to allow at each step. In this paper, we investigate the requirements and trade-offs for making this choice.Most related work chooses the viable nexthops by applying the "Downward Criterion", i.e., only adding nexthops that lead closer to the destination; or more generally by creating a Directed Acyclic Graph (DAG) for each destination. We show that a DAG's nexthop options are necessarily limited, and that, by using certain links in both directions (per destination), we can add further nexthops while still avoiding loops. Our solution LFID (LoopFree Inport-Dependent) routing, though having a slightly higher time complexity, leads to both a higher number of and shorter potential paths than related work. LFID thus protects against a higher percentage of single and multiple failures (or congestions) and comes close to the performance of arbitrary source routing.

Industrial Internet of Things (IIoT) applications, featured with data-centric innovations, are leveraging the observability, control, and analytics, as well as the safety of industrial operations. In IIoT deployments, wireless links are increasingly used in improving the operational connectivity for industrial data services, such as collecting massive process data, communicating with industrial robots, and tracking machines/parts/products on the factory floor and beyond. The wireless system design for IIoT applications is inherently a joint effort between operational technology (OT) engineers, information technology (IT) system architects, and wireless network planners. In this paper, we propose a new reference framework for the wireless system design in IIoT use cases. The framework presents a generic design process and identifies the key questions and tools of individual procedures. Specifically, we extract impact factors from distinct domains including industrial operations and environments, data service dynamics, and the IT infrastructure. We then map these factors into function clusters and discuss their respective impact on performance metrics and resource utilization strategies. Finally, discussions take place in four exemplary IIoT applications where we use the framework to identify the wireless network issues and deployment features in the continuous process monitoring, discrete system control, mobile applications, and spectrum harmonization, respectively. The goals of this work are twofold: 1) to assist OT engineers to better recognize wireless communication demands and challenges in their plants, 2) to help industrial IT specialists to come up with operative and efficient end-to-end wireless solutions to meet demanding needs in factory environments.

The main architectural problem with the current inter-domain routing model is the overloading of IP addresses due to their use for identification, location, and forwarding. This makes it hard to support the need for multi-homing, traffic engineering, and mobility while maintaining address hierarchy that is essential for scalable routing. Thus, there is a need to separate identifiers from locators. In this paper we identify architectural and protocol changes in addressing and routing needed to provide major improvements in scalability. We design a corresponding protocol solution (Address-Identifier Mapping System — AIMS) based on separation of identification and addressing, and a mechanism for mapping ID to address.

In this paper, we consider a distributed medium access control (MAC) for mobile ad-hoc networks (MANET). We propose an adaptive threshold-based medium contention scheme to exploit diversity gain in multiple dimensions, in particular, the time and user diversity. In our scheme, each node performs a c

A new generation of ATM switches with more sophisticated cell queueing and scheduling capabilities are becoming available. We discuss an effective approach to connection admission control (CAC) for the real-time variable-bit-rate (rtVBR) service category in an ATM switch with per-VC queueing and scheduling. The quality of service (QoS) requirements for rtVBR are given in terms of the cell loss ratio (CLR) and the cell delay variation (CDV). Given the rtVBR traffic descriptor and QoS parameters, we compute the capacity C/sub rtVBR/ required to support all the ATM virtual circuits (VCs) in the rtVBR category while meeting their QoS requirement. As part of the process of computing C/sub rtVBR/, we also compute a per-VC effective bandwidth used to program the scheduler. We also characterize the admissible region in the 2-class case and show that it is made up of delay-dominant and loss-dominant regions.

There have been numerous studies on congestion control for the ABR service in ATM networks. These studies typically focus on the performance and fairness of the algorithms and make simplistic assumptions regarding the switch architecture and the link scheduling. One central issue of these studies has been the computation of the fair share of the link bandwidth. On the other hand, newer generation of ATM chipsets and switches now implement per-VC queueing and scheduling that is capable of providing flow isolation as well as fair sharing of the link bandwidth among contending connections. As a result, ABR congestion control algorithms can now focus on solving the congestion control problem without unnecessarily being burdened by fairness considerations. In this paper, we take advantage of the per-VC queueing/scheduling capability of the new generation of ATM switches and develop an ABR rate-based congestion control algorithm. In contrast to most algorithms that appeared in the literature which are heuristics-based, this algorithm extends previous work (see IEEE/ACM Trans. on Networking, vol.1, no.6, p.693-707, 1993) using a control-theoretic approach and takes advantage of the per-VC queue length information to achieve a simple to implement and yet complete control of the stability, rate of convergence, and performance of ABR service. Simulation results confirm the excellent performance and fairness characteristics achieved by the algorithm.

Addresses a rate-based feedback approach to congestion control in packet switching networks where sources adjust their transmission rate in response to feedback information from the network nodes. Specifically, a controller structure and system architecture are introduced and the analysis of the resulting closed loop system is presented. Conditions for asymptotic stability are derived. A design technique for the controller gains is developed and an illustrative example is considered. The results show that, under appropriately selected control gains, a stable (nonoscillatory) operation of store-and-forward packet switching networks with feedback congestion control is possible.>