Kyoung-Don Kang

Managing deadline miss ratio and sensor data freshness in real-time databases

The demand for real-time data services is increasing in many applications including e-commerce, agile manufacturing, and telecommunications network management. In these applications, it is desirable to execute transactions within their deadlines, i.e., before the real-world status changes, using fresh (temporally consistent) data. However, meeting these fundamental requirements is challenging due to dynamic workloads and data access patterns in these applications. Further, transaction timeliness and data freshness requirements may conflict. We define average/transient deadline miss ratio and new data freshness metrics to let a database administrator specify the desired quality of real-time data services for a specific application. We also present a novel QoS management architecture for real-time databases to support the desired QoS even in the presence of unpredictable workloads and access patterns. To prevent overload and support the desired QoS, the presented architecture applies feedback control, admission control, and flexible freshness management schemes. A simulation study shows that our QoS-aware approach can achieve a near zero miss ratio and perfect freshness, meeting basic requirements for real-time transaction processing. In contrast, baseline approaches fail to support the desired miss ratio and/or freshness in the presence of unpredictable workloads and data access patterns.

A QoS-sensitive approach for timeliness and freshness guarantees in real-time databases

The demand for real-time database services has been increasing recently. Examples include sensor data fusion, decision support, Web information services, and online trading. In these applications, it is desirable to execute transactions within their deadlines using temporally consistent data. Due to the high service demand, real-time databases can be overloaded. As a result, many transactions may miss their deadlines, or data temporal consistency constraints can be violated. To address these problems, we present a QoS management scheme to support guarantees on deadline miss ratio and data freshness (temporal consistency) even in the presence of unpredictable workloads and data access patterns. Using our approach, admitted user transactions can be processed in time using fresh data. A simulation study shows that our QoS-sensitive approach can achieve a significant performance improvement, in terms of deadline miss ratio and data freshness, compared to several baseline approaches. Furthermore, our approach shows a comparable performance to the theoretical oracle that is privileged by a complete future knowledge of data accesses.

Location verification and trust management for resilient geographic routing

In this paper, we consider the security of geographic routing (GR) protocols. In GR, neighbors exchange their location information. Based on this information, a node forwards packets to the neighbor that is closest to the destination. Although GR is widely used in ad hoc and wireless sensor networks, its security has rarely been studied; there are a number of attacks that are possible on GR. In one attack, misbehaving nodes can falsify their location information. Also, malicious nodes can drop packets that they need to forward towards the destination. The first contribution of the paper is to propose a location verification algorithm to address the attacks falsifying the location information. The second contribution of the paper is to propose approaches for trust-based multi-path routing, aiming to defeat attacks on GR. We discuss the proposed approaches in detail, outlining possible attacks and defenses against them. In addition, we show, via simulation, how trust-based route selection is able to circumvent attackers and route around them. This paper summarizes and extends results reported by the authors in a previous article [K.-D.K. Nael, B. Abu-Ghazaleh, K. Liu, Towards resilient routing in WSNs, in: Proceedings of the First IEEE/ACM Workshop on QoS and Security in Wireless Networks (Q2SWinet 2005), 2005, pp. 71-78].

Dynamic localization control for mobile sensor networks

Localization is a fundamental operation in mobile and self-configuring networks such as sensor networks and mobile ad hoc networks. For example, sensor location is often critical for data interpretation. Existing research focuses on localization mechanisms: algorithms and infrastructure designed to allow the sensors to determine their location. In a mobile environment, the underlying localization mechanism must be invoked repeatedly to maintain accurate location information. We propose and investigate adaptive and predictive protocols that control the frequency of localization based on sensor mobility behavior to reduce the energy requirements for localization while bounding the localization error. In addition, we evaluate the energy-accuracy tradeoffs. Our results indicate that the proposed protocols reduce the localization energy significantly without sacrificing accuracy.

Using fuzzy logic for robust event detection in wireless sensor networks

Event detection is a central component in numerous wireless sensor network (WSN) applications. Nevertheless, the area of event description has not received enough attention. The majority of current event description and detection approaches rely on using precise values to specify event thresholds. However, we believe that crisp values cannot adequately handle the often imprecise sensor readings. In this paper we demonstrate that using fuzzy values instead of crisp ones significantly improves the accuracy of event detection. We also show that our fuzzy logic approach provides higher event detection accuracy than two well-established classification algorithms. A disadvantage of using fuzzy logic is the exponentially growing size of the fuzzy logic rule-base. As sensor nodes have limited memory, storing large rule-bases could be a challenge. To address this issue, we have developed a number of techniques that help reduce the size of the rule-base by more than 70%, while preserving the event detection accuracy.

Chronos: Feedback Control of a Real Database System Performance

It is challenging to process transactions in a timely fashion using fresh data, e.g., current stock prices, since database workloads may considerably vary due to dynamic data/resource contention. Further, transaction timeliness and data freshness requirements may compete for system resources. In this paper, we propose a novel feedback control model to support the desired data service delay by managing the size of the ready queue, which indicates the amount of the backlog in the database. We also propose a new self-adaptive update policy to adapt the freshness of cold data in a differentiated manner based on temporal data access and update patterns. Unlike most existing work on feedback control of real-time database (RTDB) performance, we actually implement and evaluate feedback control and database workload adaptation techniques in a real database testbed modeling stock trades. For performance evaluation, we undertake experiments in the testbed, which consists of thousands of client threads concurrently requesting database services for stock quotes, trades, and portfolio updates in a bursty manner. In these experiments, our database system supports the desired response time bound and data freshness, while processing a significantly larger number of transactions in time compared to the tested baselines.

Towards resilient geographic routing in WSNs

In this paper, we consider the security of geographical forwarding (GF) -- a class of algorithms widely used in ad hoc and sensor networks. In GF, neighbors exchange their location information, and a node forwards packets to the destination by picking a neighbor that moves the packet closer to the destination. There are a number of attacks that are possible on geographic forwarding. One of the attacks is predicated on misbehaving nodes falsifying their location information. The first contribution of the paper is to propose a location verification algorithm that addresses this problem. The second contribution of the paper is to propose approaches for route authentication and trust-based route selection to defeat attacks on the network. We discuss the proposed approaches in detail, outlining possible attacks and defenses against them.

An application-driven perspective on wireless sensor network security

Wireless sensor networks (WSNs) have recently attracted a lot of interest due to the range of applications they enable. Unfortunately, WSNs are exposed to numerous security threats that can adversely affect the success of important applications. Securing WSNs is challenging due to their unique nature as an application and a network, and due to their limited capabilities. In this paper, we argue that the WSN security research generally considers mechanisms that are modeled after and evaluated against abstract applications and WSN organizations. Instead, we propose that an effective solution for WSNs must be sensitive to the application and infrastructure. We propose an application-specific security context as the combination of a potential attacker¿s motivation and the WSN vulnerability. The vulnerability is a function of factors such as the sensor field, the WSN infrastructure, the application, protocols and system software, as well the accessibility and the observability of the WSN. To reduce the vulnerability, we argue that WSN design must balance traditional objectives such as energy efficiency, cost, and application level performance with security to a degree proportional to the attacker¿s motivation. We illustrate this argument via two example applications

Service differentiation in real-time main memory databases

The demand for real-time database services has been increasing. Examples include sensor data fusion, stock trading, decision support, Web information services, and data-intensive smart spaces. In these systems, it is essential to execute transactions in time using fresh (temporally consistent) data. Due to the high service demand, many transactions may miss their deadlines regardless of their importance. To address the problem, we present a service differentiation architecture for real-time databases. Transactions are classified into several service classes based on their importance. Under conditions of overload, different degrees of deadline miss ratio guarantees are provided among the service classes according to their importance. A certain data freshness guarantee is also provided for the data accessed by timely transactions which finish within their deadlines. Feedback control is applied to support the miss ratio and freshness guarantees. In a simulation study, our service differentiation approach shows a significant performance improvement compared to the baseline approaches. The specified miss ratio and freshness are supported even in the presence of unpredictable workloads and data access patterns.

Hop-by-hop congestion control and load balancing in wireless sensor networks

Due to the relatively high node density and source-to-sink communication pattern, wireless sensor networks (WSNs) are subject to congestion and packet losses. Further, the availability of low-cost hardware, such as Cyclops cameras, is promoting wireless multimedia sensing to support, for example, visual surveillance. As a result, congestion control is becoming more critical in WSNs. In this paper, we present a lightweight distributed congestion control method in WSNs. We develop new metrics to detect congestion in each node by considering the queue lengths and channel conditions observed in the one-hop neighborhood. Based on the estimated level of congestion, each node dynamically adapts its packet transmission rate and balance the load among the one-hop neighbors to avoid creating congestion and bottleneck nodes. In a simulation study performed in OMNeT++, our approach significantly enhances the end-to-end (e2e) packet delivery ratio and reduces the e2e delay without increasing the total energy consumption compared to the tested baseline approach.