Rolf Stadler

Resource Management in Clouds: Survey and Research Challenges

Abstract Resource management in a cloud environment is a hard problem, due to: the scale of modern data centers; the heterogeneity of resource types and their interdependencies; the variability and unpredictability of the load; as well as the range of objectives of the different actors in a cloud ecosystem. Consequently, both academia and industry began significant research efforts in this area. In this paper, we survey the recent literature, covering 250+ publications, and highlighting key results. We outline a conceptual framework for cloud resource management and use it to structure the state-of-the-art review. Based on our analysis, we identify five challenges for future investigation. These relate to: providing predictable performance for cloud-hosted applications; achieving global manageability for cloud systems; engineering scalable resource management systems; understanding economic behavior and cloud pricing; and developing solutions for the mobile cloud paradigm .

Key research challenges in network management

Although network management has always played a key role for industry, it only recently received a similar level of attention from many research communities, accelerated by funding opportunities from new initiatives, including the FP7 Program in Europe and GENI/FIND in the United States. Work is ongoing to assess the state of the art and identify the challenges for future research in the field, and this article contributes to this discussion. It presents major findings from a two-day workshop organized jointly by the IRTF/NMRG and the EMANICS Network of Excellence, at which researchers, operators, vendors, and technology developers discussed the research directions to be pursued over the next five years. The workshop identified several topic areas, including management architectures, distributed real-time monitoring, data analysis and visualization, ontologies, economic aspects of management, uncertainty and probabilistic approaches, as well as understanding the behavior of managed systems.

A-GAP: An Adaptive Protocol for Continuous Network Monitoring with Accuracy Objectives

We present A-GAP, a novel protocol for continuous monitoring of network state variables, which aims at achieving a given monitoring accuracy with minimal overhead. Network state variables are computed from device counters using aggregation functions, such as SUM, AVERAGE and MAX. The accuracy objective is expressed as the average estimation error. A-GAP is decentralized and asynchronous to achieve robustness and scalability. It executes on an overlay that interconnects management processes on the devices. On this overlay, the protocol maintains a spanning tree and updates the network state variables through incremental aggregation. Based on a stochastic model, it dynamically configures local filters that control whether an update is sent towards the root of the tree. We evaluate A-GAP through simulation using real traces and two different types of topologies of up to 650 nodes. The results show that we can effectively control the trade-off between accuracy and protocol overhead, and that the overhead can be reduced by almost two orders of magnitude when allowing for small errors. The protocol quickly adapts to a node failure and exhibits short spikes in the estimation error. Lastly, it can provide an accurate estimate of the error distribution in real-time.

Gossip-based resource management for cloud environments

We address the problem of resource management for a large-scale cloud environment that hosts sites. Our contribution centers around outlining a distributed middleware architecture and presenting one of its key elements, a gossip protocol that meets our design goals: fairness of resource allocation with respect to hosted sites, efficient adaptation to load changes and scalability in terms of both the number of machines and sites. We formalize the resource allocation problem as that of dynamically maximizing the cloud utility under CPU and memory constraints. While we can show that an optimal solution without considering memory constraints is straightforward (but not useful), we provide an efficient heuristic solution for the complete problem instead. We evaluate the protocol through simulation and find its performance to be well-aligned with our design goals.

A Gossip Protocol for Dynamic Resource Management in Large Cloud Environments

We address the problem of dynamic resource management for a large-scale cloud environment. Our contribution includes outlining a distributed middleware architecture and presenting one of its key elements: a gossip protocol that (1) ensures fair resource allocation among sites/applications, (2) dynamically adapts the allocation to load changes and (3) scales both in the number of physical machines and sites/applications. We formalize the resource allocation problem as that of dynamically maximizing the cloud utility under CPU and memory constraints. We first present a protocol that computes an optimal solution without considering memory constraints and prove correctness and convergence properties. Then, we extend that protocol to provide an efficient heuristic solution for the complete problem, which includes minimizing the cost for adapting an allocation. The protocol continuously executes on dynamic, local input and does not require global synchronization, as other proposed gossip protocols do. We evaluate the heuristic protocol through simulation and find its performance to be well-aligned with our design goals.

Robust monitoring of network-wide aggregates through gossiping

We investigate the use of gossip protocols for continuous monitoring of network-wide aggregates under crash failures. Aggregates are computed from local management variables using functions such as SUM, MAX, or AVERAGE. For this type of aggregation, crash failures offer a particular challenge due to the problem of mass loss, namely, how to correctly account for contributions from nodes that have failed. In this paper we give a partial solution. We present G-GAP, a gossip protocol for continuous monitoring of aggregates, which is robust against failures that are discontiguous in the sense that neighboring nodes do not fail within a short period of each other. We give formal proofs of correctness and convergence, and we evaluate the protocol through simulation using real traces. The simulation results suggest that the design goals for this protocol have been met. For instance, the tradeoff between estimation accuracy and protocol overhead can be controlled, and a high estimation accuracy (below some 5% error in our measurements) is achieved by the protocol, even for large networks and frequent node failures. Further, we perform a comparative assessment of GGAP against a tree-based aggregation protocol using simulation. Surprisingly, we find that the tree-based aggregation protocol consistently outperforms the gossip protocol for comparative overhead, both in terms of accuracy and robustness.

Service Middleware for Self-Managing Large-Scale Systems

Resource management poses particular challenges in large-scale systems, such as server clusters that simultaneously process requests from a large number of clients. A resource management scheme for such systems must scale both in the in the number of cluster nodes and the number of applications the cluster supports. Current solutions do not exhibit both of these properties at the same time. Many are centralized, which limits their scalability in terms of the number of nodes, or they are decentralized but rely on replicated directories, which also reduces their ability to scale. In this paper, we propose novel solutions to request routing and application placement- two key mechanisms in a scalable resource management scheme. Our solution to request routing is based on selective update propagation, which ensures that the control load on a cluster node is independent of the system size. Application placement is approached in a decentralized manner, by using a distributed algorithm that maximizes resource utilization and allows for service differentiation under overload. The paper demonstrates how the above solutions can be integrated into an overall design for a peer-to-peer management middleware that exhibits properties of self-organization. Through complexity analysis and simulation, we show to which extent the system design is scalable. We have built a prototype using accepted technologies and have evaluated it using a standard benchmark. The testbed measurements show that the implementation, within the parameter range tested, operates efficiently, quickly adapts to a changing environment and allows for effective service differentiation by a system administrator.

An architecture for broadband virtual networks under customer control

Emerging ATM-based virtual private network (VPN) services offer customers a flexible way to interconnect customer premises networks (CPNs) via high-speed links. Compared with traditional leased lines, these services allow for rapid provisioning of VPN bandwidth through cooperative control between customer and provider. Customers can dynamically renegotiate the VPN bandwidth according to their current needs, paying only for the resources they actually use. In order to meet the various requirements and demands of different classes of VPN customers, a VPN provider must provide customers with the flexibility to choose their own control schemes and objectives. The focus of this paper is on enhancing the customers capability of controlling a VPN. First, we propose a new scheme for a broadband VPN service, which is based on the virtual path group (VPG) concept. In our scheme, the customer performs VP control operations without interacting with the VPN provider, thus enabling the following merits: (1) the customer can share bandwidth among VPs that traverse the same physical network link in the providers domain, thus using the VPN bandwidth more efficiently; (2) customers can perform VP control operations according to their own requirements and control objectives. Second, we outline an architecture for a customer-operated control system, which utilizes a VPG-based VPN service. The system is structured into three layers of control, which execute on different time scales. The functionalities of these layers are call processing, VP control, and VPN control, respectively. Finally, we evaluate the effectiveness of the control system, with respect to VP control.

Robust Monitoring of Network-wide Aggregates through Gossiping

We investigate the use of gossip protocols for continuous monitoring of network-wide aggregates under crash failures. Aggregates are computed from local management variables using functions such as SUM, MAX, or AVERAGE. For this type of aggregation, crash failures offer a particular challenge due to the problem of mass loss, namely, how to correctly account for contributions from nodes that have failed. In this paper we give a partial solution. We present G-GAP, a gossip protocol for continuous monitoring of aggregates, which is robust against failures that are discontiguous in the sense that neighboring nodes do not fail within a short period of each other. We give formal proofs of correctness and convergence, and we evaluate the protocol through simulation using real traces. The simulation results suggest that the design goals for this protocol have been met. For instance, the tradeoff between estimation accuracy and protocol overhead can be controlled, and a high estimation accuracy (below some 5% error in our measurements) is achieved by the protocol, even for large networks and frequent node failures. Further, we perform a comparative assessment of GGAP against a tree-based aggregation protocol using simulation. Surprisingly, we find that the tree-based aggregation protocol consistently outperforms the gossip protocol for comparative overhead, both in terms of accuracy and robustness.

Customer management and control of broadband VPN services

We present an architecture for customer management and control of a broadband VPN service. The architecture is aimed at giving the VPN customer a high level of control over the traffic on the VPN, such that end-to-end requirements for the customer’s enterprise network can be met. We describe how different control and management objectives can be achieved with this architecture. Its design includes a generic resource controller, which can be specialized in order to realize a large class of control schemes, following a customer’s specific requirements. We have implemented a prototype of this architecture on a high-performance emulation platform. The prototype allows us to validate the management and control functionality of the customer control system and to demonstrate the performance characteristics of different realizations of the architecture.