Recreational Food Service is Big Business

In the analysis - Recreational Food Service Is Big Business - by Gary Horvath, President, Recreational Foodservice Division, Service America Corporation and Mickey Warner, Associate Professor School of Hospitality Management at Florida International University, Horvath and Warner initially state: “Recreational food service is very different from routine food service management. The authors review the market and the management planning and challenges that create that difference.” Recreational food is loosely defined by the authors as food for special events. These can be one-time events, repeated events that are not on a fixed schedule [i.e. concerts], weekly events such as football-baseball-or basketball games, or other similar venues. Concessions are a large part of these fan based settings. “An anticipated 101,000 fans at a per capita spending of $5-6 [were expected]. A typical concessions menu of hot dogs, popcorn, soda, beer, snacks, novelty foods, candy, and tobacco products comprises this market segment,” say Horvath and Warner in reference to the Super-Bowl XXI football championship game, held in Rose Bowl stadium in Pasadena, California, on January 25, 1987. Some of the article is based upon that event. These food service efforts focus on the individual fan, but do extend to the corporate-organizational level as well. Your authors will have you know that catering is definitely a part of this equation. The monies spent and earned are phenomenal. “Special events of this type attract numerous corporate catering opportunities for companies entertaining VIP guest lists,” the authors inform. “Hospitality tents usually consist of a pregame cocktail party and buffet and a post-game celebration with musical entertainment held in lavishly decorated tents erected at the site. In this case a total of 5,000 covers, at a price of $200 each, for 12-15 separate parties were anticipated.” Horvath and Warner also want you to know that novelties and souvenirs make up an essential part of this, the recreational food service market. “Novelties and souvenirs are a primary market and source of revenue for every stadium food service operator,” say Horvath and Warner. The term, “per capita spending is the measurement used by the industry to evaluate sales potential per attendee at an event,” say the authors. Of course, with the solid revenue figures involved as well as the number of people anticipated for such events, planning is crucial, say Horvath and Warner. Training of staff, purchasing and supply, money and banking, facility access, and equipment, are a few of the elements to be negotiated. Through both graphs and text, Horvath and Warner do provide a fairly detailed outline of what a six-step event plan consists of.

Fuzzy Modeling and Control Based Virtual Machine Resource Management

Virtual machines (VMs) are powerful platforms for building agile datacenters and emerging cloud systems. However, resource management for a VM-based system is still a challenging task. First, the complexity of application workloads as well as the interference among competing workloads makes it difficult to understand their VMs’ resource demands for meeting their Quality of Service (QoS) targets; Second, the dynamics in the applications and system makes it also difficult to maintain the desired QoS target while the environment changes; Third, the transparency of virtualization presents a hurdle for guest-layer application and host-layer VM scheduler to cooperate and improve application QoS and system efficiency. This dissertation proposes to address the above challenges through fuzzy modeling and control theory based VM resource management. First, a fuzzy-logic-based nonlinear modeling approach is proposed to accurately capture a VM’s complex demands of multiple types of resources automatically online based on the observed workload and resource usages. Second, to enable fast adaption for resource management, the fuzzy modeling approach is integrated with a predictive-control-based controller to form a new Fuzzy Modeling Predictive Control (FMPC) approach which can quickly track the applications’ QoS targets and optimize the resource allocations under dynamic changes in the system. Finally, to address the limitations of black-box-based resource management solutions, a cross-layer optimization approach is proposed to enable cooperation between a VM’s host and guest layers and further improve the application QoS and resource usage efficiency. The above proposed approaches are prototyped and evaluated on a Xen-based virtualized system and evaluated with representative benchmarks including TPC-H, RUBiS, and TerraFly. The results demonstrate that the fuzzy-modeling-based approach improves the accuracy in resource prediction by up to 31.4% compared to conventional regression approaches. The FMPC approach substantially outperforms the traditional linear-model-based predictive control approach in meeting application QoS targets for an oversubscribed system. It is able to manage dynamic VM resource allocations and migrations for over 100 concurrent VMs across multiple hosts with good efficiency. Finally, the cross-layer optimization approach further improves the performance of a virtualized application by up to 40% when the resources are contended by dynamic workloads.

Approaches to Provisioning Network Topology of Virtual Machines in Cloud Systems

The current infrastructure as a service (IaaS) cloud systems, allow users to load their own virtual machines. However, most of these systems do not provide users with an automatic mechanism to load a network topology of virtual machines. In order to specify and implement the network topology, we use software switches and routers as network elements. Before running a group of virtual machines, the user needs to set up the system once to specify a network topology of virtual machines. Then, given the user’s request for running a specific topology, our system loads the appropriate virtual machines (VMs) and also runs separated VMs as software switches and routers. Furthermore, we have developed a manager that handles physical hardware failure situations. This system has been designed in order to allow users to use the system without knowing all the internal technical details.