Junwhan Kim

Opportunistic real-time routing in multi-hop wireless sensor networks

Wireless sensor networks (WSNs) are subject to significant resource constraints. Particularly, routing protocols for low-rate WSNs suffer from maintaining routing metrics and stable links of paths. Even though opportunistic routing protocols are well-suited to WSNs, they have some weaknesses for supporting real-time data and low power consumption. This paper proposes a new routing protocol called opportunistic real time routing (or ORTR) that guarantees delivery of data under time constraints with efficient power consumption. In order to satisfy time requirements, an area where real-time data must be delivered is defined with effective transmission power and a relay node within the area is selected for the purpose of balancing overall energy levels. We compare existing routing protocols against ORTR through a set of simulation experiments. Our simulation results illustrate that ORTR provides guaranteed real-time service with optimal transmission power without degrading the energy balance.

On transactional scheduling in distributed transactional memory ystems

We present a distributed transactional memory (TM) scheduler called Bi-interval that optimizes the execution order of transactional operations to minimize conflicts. Bi-interval categorizes concurrent requests for a shared object into read and write intervals to maximize the parallelism of reading transactions. This allows an object to be simultaneously sent to nodes of reading transactions (in a data flow TM model), improving transactional makespan. We show that Bi-interval improves the makespan competitive ratio of the Relay distributed TM cache coherence protocol to O(log(n)) for the worst-case and Θlog(n - k) for the average-case, for n nodes and k reading transactions. Our implementation studies confirm Bi-intervals throughput improvement by as much as 200% ∼ 30%, over cache-coherence protocol-only distributed TM.

Scheduling Transactions in Replicated Distributed Software Transactional Memory

Distributed software transactional memory (DTM) is an emerging, alternative concurrency control model for distributed systems that promises to alleviate the difficulties of lock-based distributed synchronization. Object replication can improve concurrency and achieve fault-tolerance in DTM, but may incur high communication overhead (in metric-space networks) to ensure one-copy serializability. We consider metric-space networks and develop a cluster-based object replication model for DTM. In this model, object replicas are distributed to clusters of nodes, where clusters are determined based on distance between nodes, to maximize locality and fault-tolerance and to minimize communication overhead. We develop a transactional scheduler for this model, called CTS. CTS enqueues live transactions and identifies some of the transactions that must be aborted in advance to enhance concurrency of the other transactions over clusters, reducing a significant number of future conflicts. Our implementation and experimental evaluation reveals that CTS improves transactional throughput over state-of-the-art replicated DTM solutions by as much as (average) 1.55x and 1.73x under low and high contention, respectively.

Enhancing concurrency in distributed transactional memory through commutativity

Distributed software transactional memory is an emerging, alternative concurrency control model for distributed systems promising to alleviate the difficulties of lock-based distributed synchronization. We consider the multi-versioning (MV) model to avoid unnecessary aborts. MV schemes inherently guarantee commits of read-only transactions, but limit the concurrency of write transactions. In this paper we propose CRF (Commutative Requests First), a new scheduler tailored for enhancing concurrency of write transactions. CRF relies on the notion of commutative transactions, namely conflicting transactions that leave the state of the shared data-set consistent even if validated and committed concurrently. CRF is responsible to detect conflicts among commutative and non-commutative write transactions and then schedules them according to the execution state. We assess the goodness of the approach by an extensive evaluation of a fully implementation of CRF. The tests reveal that CRF improves throughput over a state-of-the-art DTM solution.

Integrated Multi-Network Modeling Environment for Spectrum Management

We describe a first principles based integrated modeling environment to study urban socio-communication networks which represent not just the physical cellular communication network, but also urban populations carrying digital devices interacting with the cellular network. The modeling environment is designed specifically to understand spectrum demand and dynamic cellular network traffic. One of its key features is its ability to support individual-based models at highly resolved spatial and temporal scales. We have instantiated the modeling environment by developing detailed models of population mobility, device ownership, calling patterns and call network. By composing these models using an appropriate in-built workflow, we obtain an integrated model that represents a dynamic socio-communication network for an entire urban region. In contrast with earlier papers that typically use proprietary data, these models use open source and commercial data sets. The dynamic model represents for a normative day, every individual in an entire region, with detailed demographics, a minute-by-minute schedule of each persons activities, the locations where these activities take place, and calling behavior of every individual. As an illustration of the applicability of the modeling environment, we have developed such a dynamic model for Portland, Oregon comprising of approximately 1.6 million individuals. We highlight the unique features of the models and the modeling environment by describing three realistic case studies.

Rate Adaptation Scheme for Slot Reservation in WiMedia MAC

The rate adaptation technique is an effective way to reliably transmit data in wireless networks. In this paper, we propose a novel rate adaptation scheme using not only range measurement operation (RMO) for measuring distance, but also average receive signal strength indication (RSSI) values for recognizing further obstacles. A decided data rate based on an estimated channel condition is used for both reliable data transmission and slot reservation in distributed reservation protocol (DRP) of WiMedia MAC. Last, we show the throughput measurement of our scheme working on WiMedia MAC.

Scheduling Closed-Nested Transactions in Distributed Transactional Memory

Distributed software transactional memory (D-STM) is an emerging, alternative concurrency control model for distributed systems that promises to alleviate the difficulties of lock-based distributed synchronization -- e.g., distributed deadlocks, live locks, and lock convoying. We consider Herlihy and Suns dataflow D-STM model, where objects are migrated to invoking transactions, and the \emph{closed nesting} model of managing inner (distributed) transactions. We present a transactional scheduler called, reactive transactional scheduler (or RTS) to boost the throughput of closed-nested transactions. RTS determines whether a conflicting parent transaction must be aborted or enqueued according to the level of contention. If a transaction is enqueued, its nested inner transactions do not have to retrieve objects again, resulting in reduced communication delays. Our implementation of RTS in the HyFlow D-STM framework and experimental evaluations reveal that RTS improves throughput over D-STM without RTS, by as much as 88%.

Human Initiated Cascading Failures in Societal Infrastructures

In this paper, we conduct a systematic study of human-initiated cascading failures in three critical inter-dependent societal infrastructures due to behavioral adaptations in response to a crisis. We focus on three closely coupled socio-technical networks here: (i) cellular and mesh networks, (ii) transportation networks and (iii) mobile call networks. In crises, changes in individual behaviors lead to altered travel, activity and calling patterns, which influence the transport network and the loads on wireless networks. The interaction between these systems and their co-evolution poses significant technical challenges for representing and reasoning about these systems. In contrast to system dynamics models for studying these interacting infrastructures, we develop interaction-based models in which individuals and infrastructure elements are represented in detail and are placed in a common geographic coordinate system. Using the detailed representation, we study the impact of a chemical plume that has been released in a densely populated urban region. Authorities order evacuation of the affected area, and this leads to individual behavioral adaptation wherein individuals drop their scheduled activities and drive to home or pre-specified evacuation shelters as appropriate. They also revise their calling behavior to communicate and coordinate among family members. These two behavioral adaptations cause flash-congestion in the urban transport network and the wireless network. The problem is exacerbated with a few, already occurring, road closures. We analyze how extended periods of unanticipated road congestion can result in failure of infrastructures, starting with the servicing base stations in the congested area. A sensitivity analysis on the compliance rate of evacuees shows non-intuitive effect on the spatial distribution of people and on the loading of the base stations. For example, an evacuation compliance rate of 70% results in higher number of overloaded base stations than the evacuation compliance rate of 90%.

Link Adaptation Strategy on Transmission Rate and Power Control in IEEE 802.11 WLANs

Link Adaptation techniques, such as rate adaptation and power control, aim at reliable data transmission through maintaining link quality. In order to do that, we measure the performance of IEEE 802.11 Wireless LAN (WLAN) in real environments that produce unexpected interference from neighbor access points or electronic devices. In this paper, we propose a novel strategy for the link adaptation technique in WLAN MAC. The new strategy provides two decisions to estimate the link condition and to manage both the transmission rate and power. Finally, we show reliable transmission through the throughput measurement using the MAC we designed.

Scheduling Open-Nested Transactions in Distributed Transactional Memory

Distributed software transactional memory (D-STM) is an emerging, alternative concurrency control model for distributed systems that promises to alleviate the difficulties of lock-based distributed synchronization -- e.g., distributed deadlocks, live locks, and lock convoying. We consider Herlihy and Suns dataflow D-STM model, where objects are migrated to invoking transactions, and the \emph{closed nesting} model of managing inner (distributed) transactions. We present a transactional scheduler called, reactive transactional scheduler (or RTS) to boost the throughput of closed-nested transactions. RTS determines whether a conflicting parent transaction must be aborted or enqueued according to the level of contention. If a transaction is enqueued, its nested inner transactions do not have to retrieve objects again, resulting in reduced communication delays. Our implementation of RTS in the HyFlow D-STM framework and experimental evaluations reveal that RTS improves throughput over D-STM without RTS, by as much as 88%.