OCDec 1, 2011
Explicit Characterization of Stability Region for Stationary Multi-Queue Multi-Server SystemsHassan Halabian, Ioannis Lambadaris, Chung-Horng Lung
In this paper, we characterize the network stability region (capacity region) of multi-queue multi-server (MQMS) queueing systems with stationary channel distribution and stationary arrival processes. The stability region is specified by a finite set of linear inequalities. We first show that the stability region is a polytope characterized by the finite set of its facet defining hyperplanes. We explicitly determine the coefficients of the linear inequalities describing the facet defining hyperplanes of the stability region polytope. We further derive the necessary and sufficient conditions for the stability of the system for general arrival processes with finite first and second moments. For the case of stationary arrival processes, the derived conditions characterize the system stability region. Furthermore, we obtain an upper bound for the average queueing delay of Maximum Weight (MW) server allocation policy which has been shown in the literature to be a throughput optimal policy for MQMS systems. Using a similar approach, we can characterize the stability region for a fluid model MQMS system. However, the stability region of the fluid model system is described by an infinite number of linear inequalities since in this case the stability region is a convex surface. We present an example where we show that in some cases depending on the channel distribution, the stability region can be characterized by a finite set of non-linear inequalities instead of an infinite number of linear inequalities.
ITDec 6, 2011
On the Stability Region of Multi-Queue Multi-Server Queueing Systems with Stationary Channel DistributionHassan Halabian, Ioannis Lambadaris, Chung-Horng Lung
In this paper, we characterize the stability region of multi-queue multi-server (MQMS) queueing systems with stationary channel and packet arrival processes. Toward this, the necessary and sufficient conditions for the stability of the system are derived under general arrival processes with finite first and second moments. We show that when the arrival processes are stationary, the stability region form is a polytope for which we explicitly find the coefficients of the linear inequalities which characterize the stability region polytope.
OCDec 6, 2011
Delay Optimal Server Assignment to Symmetric Parallel Queues with Random ConnectivitiesHassan Halabian, Ioannis Lambadaris, Chung-Horng Lung
In this paper, we investigate the problem of assignment of $K$ identical servers to a set of $N$ parallel queues in a time slotted queueing system. The connectivity of each queue to each server is randomly changing with time; each server can serve at most one queue and each queue can be served by at most one server per time slot. Such queueing systems were widely applied in modeling the scheduling (or resource allocation) problem in wireless networks. It has been previously proven that Maximum Weighted Matching (MWM) is a throughput optimal server assignment policy for such queueing systems. In this paper, we prove that for a symmetric system with i.i.d. Bernoulli packet arrivals and connectivities, MWM minimizes, in stochastic ordering sense, a broad range of cost functions of the queue lengths including total queue occupancy (or equivalently average queueing delay).
AIMay 15
Context, Reasoning, and Hierarchy: A Cost-Performance Study of Compound LLM Agent Design in an Adversarial POMDPIgor Bogdanov, Chung-Horng Lung, Thomas Kunz et al.
Deploying compound LLM agents in adversarial, partially observable sequential environments requires navigating several design dimensions: (1) what the agent sees, (2) how it reasons, and (3) how tasks are decomposed across components. Yet practitioners lack guidance on which design choices improve performance versus merely increase inference costs. We present a controlled study of compound LLM agent design in CybORG CAGE-2, a cyber defense environment modeled as a Partially Observable Markov Decision Process (POMDP). Reward is non-positive, so all configurations operate in a failure-mitigation mode. Our evaluation spans five model families, six models, and twelve configurations (3,475 episodes) with token-level cost accounting. We vary context representation (raw observations vs. a deterministic state-tracking layer with compressed history), deliberation (self-questioning, self-critique, and self-improvement tools, with optional chain-of-thought prompting), and hierarchical decomposition (monolithic ReAct vs. delegation to specialized sub-agents). We find that: (1) Programmatic state abstraction delivers the largest returns per token spent (RPTS), improving mean return by up to 76% over raw observations. (2) Distributing deliberation tools across a hierarchy degrades performance relative to hierarchy alone for all five model families, reaching up to 3.4$\times$ worse mean return while using 1.8-2.7$\times$ more tokens. We call this destructive pattern a deliberation cascade. (3) Hierarchical decomposition without deliberation achieves the best absolute performance for most models, and context engineering is generally more cost-effective than deliberation. These findings suggest a design principle for structured adversarial POMDPs: invest in programmatic infrastructure and clean task decomposition rather than deeper per-agent reasoning, as these strategies can interfere when combined.
AIMay 15
FORGE: Self-Evolving Agent Memory With No Weight Updates via Population BroadcastIgor Bogdanov, Chung-Horng Lung, Thomas Kunz et al.
Can LLM agents improve decision-making through self-generated memory without gradient updates? We propose FORGE (Failure-Optimized Reflective Graduation and Evolution), a staged, population-based protocol that evolves prompt-injected natural-language memory for hierarchical ReAct agents. FORGE wraps a Reflexion-style inner loop, where a dedicated reflection agent (using the same underlying LLM, no distillation from a stronger model) converts failed trajectories into reusable knowledge artifacts: textual heuristics (Rules), few-shot demonstrations (Examples), or both (Mixed), with an outer loop that propagates the best-performing instance's memory to the population between stages and freezes converged instances via a graduation criterion. We evaluate on CybORG CAGE-2, a stochastic network-defense POMDP at a 30-step horizon against the B-line attacker, where all four tested LLM families (Gemini-2.5-Flash-Lite, Grok-4-Fast, Llama-4-Maverick, Qwen3-235B) exhibit strongly negative, heavy-tailed zero-shot rewards. Compared against both a zero-shot baseline and a Reflexion baseline (isolated single-stream learning), FORGE improves average evaluation return by 1.7-7.7$\times$ over zero-shot and by 29-72% over Reflexion in all 12 model-representation conditions, reducing major-failure rates (below $-100$) to as low as $\sim$1%. We find that (1) population broadcast is critical mechanism, with a no-graduation ablation confirming that broadcast carries the performance gains while graduation primarily saves compute; (2) Examples achieves the strongest returns for three of four models, Rules offers the best cost-reliability profile with $\sim$40% fewer tokens; and (3) weaker baseline models benefit disproportionately, suggesting FORGE may mitigate capability gaps rather than amplify strong models. All evidence is confined to CAGE-2 B-line; cross-family findings are directional evidence.
CRApr 29, 2021
Integrating 6LoWPAN Security with RPL Using The Chained Secure Mode FrameworkAhmed Raoof, Chung-Horng Lung, Ashraf Matrawy
The IPv6 over Low-powered Wireless Personal Area Network (6LoWPAN) protocol was introduced to allow the transmission of Internet Protocol version 6 (IPv6) packets using the smaller-size frames of the IEEE 802.15.4 standard, which is used in many Internet of Things (IoT) networks. The primary duty of the 6LoWPAN protocol is packet fragmentation and reassembly. However, the protocol standard currently does not include any security measures, not even authenticating the fragments immediate sender. This lack of immediate-sender authentication opens the door for adversaries to launch several attacks on the fragmentation process, such as the buffer-reservation attacks that lead to a Denial of Service (DoS) attack and resource exhaustion of the victim nodes. This paper proposes a security integration between 6LoWPAN and the Routing Protocol for Low Power and Lossy Networks (RPL) through the Chained Secure Mode (CSM) framework as a possible solution. Since the CSM framework provides a mean of immediate-sender trust, through the use of Network Coding (NC), and an integration interface for the other protocols (or mechanisms) to use this trust to build security decisions, 6LoWPAN can use this integration to build a chain-of-trust along the fragments routing path. A proof-of-concept implementation was done in Contiki Operating System (OS), and its security and performance were evaluated against an external adversary launching a buffer-reservation attack. The results from the evaluation showed significant mitigation of the attack with almost no increase in power consumption, which presents the great potential for such integration to secure the forwarding process at the 6LoWPAN Adaptation Layer
NIFeb 11, 2021
Securing RPL using Network Coding: The Chained Secure Mode (CSM)Ahmed Raoof, Chung-Horng Lung, Ashraf Matrawy
As the de facto routing protocol for many Internet of Things (IoT) networks nowadays, and to assure the confidentiality and integrity of its control messages, the Routing Protocol for Low Power and Lossy Networks (RPL) incorporates three modes of security: the Unsecured Mode (UM), Preinstalled Secure Mode (PSM), and the Authenticated Secure Mode (ASM). While the PSM and ASM are intended to protect against external routing attacks and some replay attacks (through an optional replay protection mechanism), recent research showed that RPL in PSM is still vulnerable to many routing attacks, both internal and external. In this paper, we propose a novel secure mode for RPL, the Chained Secure Mode (CSM), based on the concept of intraflow Network Coding (NC). The CSM is designed to enhance RPL resilience and mitigation capability against replay attacks while allowing the integration with external security measures such as Intrusion Detection Systems (IDSs). The security and performance of the proposed CSM were evaluated and compared against RPL in UM and PSM (with and without the optional replay protection) under several routing attacks: the Neighbor attack (NA), Wormhole (WH), and CloneID attack (CA), using average packet delivery rate (PDR), End-to-End (E2E) latency, and power consumption as metrics. It showed that CSM has better performance and more enhanced security than both the UM and PSM with the replay protection, while mitigating both the NA and WH attacks and significantly reducing the effect of the CA in the investigated scenarios.
NIMay 30, 2020
Introducing Network Coding to RPL: The Chained Secure Mode (CSM)Ahmed Raoof, Chung-Horng Lung, Ashraf Matrawy
The current standard of Routing Protocol for Low Power and Lossy Networks (RPL) incorporates three modes of security: the Unsecured Mode (UM), Preinstalled Secure Mode (PSM), and the Authenticated Secure Mode (ASM). While the PSM and ASM are intended to protect against external routing attacks and some replay attacks (through an optional replay protection mechanism), recent research showed that RPL in PSM is still vulnerable to many routing attacks, both internal and external. In this paper, we propose a novel secure mode for RPL, the Chained Secure Mode (CSM), based on the concept of intraflow Network Coding. The main goal of CSM is to enhance RPL resilience against replay attacks, with the ability to mitigate some of them. The security and performance of a proof-of-concept prototype of CSM were evaluated and compared against RPL in UM and PSM (with and without the optional replay protection) in the presence of Neighbor attack as an example. It showed that CSM has better performance and more enhanced security compared to both the UM and PSM with the replay protection. On the other hand, it showed a need for a proper recovery mechanism for the case of losing a control message.
CRMay 24, 2019
Secure Routing in IoT: Evaluation of RPL Secure Mode under AttacksAhmed Raoof, Ashraf Matrawy, Chung-Horng Lung
As the Routing Protocol for Low Power and Lossy Networks (RPL) became the standard for routing in the Internet of Things (IoT) networks, many researchers had investigated the security aspects of this protocol. However, no work (to the best of our knowledge) has investigated the use of the security mechanisms included in the protocol standard, due to the fact that there was no implementation for these features in any IoT operating system yet. A partial implementation of RPL security mechanisms was presented recently for Contiki operating system (by Perazzo et al.), which provided us with the opportunity to examine RPL security mechanisms. In this paper, we investigate the effects and challenges of using RPL security mechanisms under common routing attacks. First, a comparison of RPL performance, with and without its security mechanisms, under three routing attacks (Blackhole, Selective- Forward, and Neighbor attacks) is conducted using several metrics (e.g., average data packet delivery rate, average data packet delay, average power consumption... etc.) Based on the observations from this comparison, we came with few suggestions that could reduce the effects of such attacks, without having added security mechanisms for RPL.